Technical Delivery Manager ( Actimize ) - Comp Tech – VP2

Consultant, Data Analytics & Reporting-Food

Senior Production Support Engineer – IDM Engineering (VP2)

Software Engineer AI

AVP, Digital Analytics

SAP Basis Engineer

Manager, Data Engineering

Sr. Software Engineer - Ag & Trading .Net

Senior Data Scientist - Machine Learning

AVP – Model Ops Engineer

Responsibilities: <ul><li>Plan technical deliverables (including any system enhancements and upgrades) to meet project’s requirements within allocated budget and schedule</li><li>Plan &amp; collaborate across different application teams to manage technical dependencies of the solution</li><li>Plan, monitor and manage risks/issues related to technical delivery</li><li>Provide status update related to technical delivery to Project Manager (PM)/ Program Manager</li><li>Partner with System Analysts, Functional Business Analysts and SME’s to collate, understand and finalize functional and technical requirements</li><li>Provide Systems input to specification phase (effort estimates, high level delivery plan) based on impact assessment etc</li><li>Partner with Development Manager in managing application teams to build the enhancements</li><li>Partner with Test Manager to ensure completion of System Integration Testing (SIT), User Acceptance Testing (UAT), performance / load testing and application security testing with quality results</li><li>Prepare and manage technical implementation plan across application teams - coordinate technical implementation activities across application teams to ensure non-event production cutover and adequate post implementation support</li><li>Escalate issues that impacts project schedule on timely basis and propose workarounds/resolutions</li><li>Provide timely updates and report to management.</li></ul> Requirements: <ul><li>Degree in Computer Science, Engineering or similar domain; Additional professional/technical qualifications will be advantageous although not mandatory</li><li>Proven working experience in project delivery or equivalent role with at least 6 years’ relevant experience in large and complex organizations preferably in the area of Banking and Finance.</li><li>Leadership experience in managing IT delivery teams and implementing large-scale project</li><li>Experience in actual systems development work, with prior coding, functional and technical specifications, systems development and testing experience Tools - JIRA, Confluence, MS Project, Excel, Visio</li><li>Good knowledge in AML policies, procedures, products and industry practices preferred</li><li>Good understanding and experience in software development cycle (Waterfall or Agile best practices)</li><li>Highly effective communicating with technical stakeholders, proficient communicating with non-technical stakeholders</li><li>Good problem solving, analytical, synthesis, system thinking and solutioning skills</li><li>Strong negotiation skills and vendor management skills</li><li>Experience in vendor product management will be an added advantage</li><li>Proficient knowledge in SQL/Oracle and/or Compliance related capabilities</li><li>Experience with UNIX and/or Windows operating system will be an added advantage</li></ul>

Responsibilities: <ul><li>Data Analysis: Collects, transforms, and analyzes data from multiple sources to identify trends, patterns, anomalies, and actionable insights that support reporting, performance tracking, and decision making.</li><li>Reporting &amp; Visualization: Implements detailed reports and dashboards using various tools, designs and completes data visualizations to communicate moderately complex data clearly.</li><li>Data Modeling &amp; Automation: Supports data models, reporting logic, and workflow automation, while identifying and implementing opportunities to improve data collection and reporting processes using standard data management and reporting practices.</li><li>Advanced Analytics Awareness: Familiarity with predictive analytics, AI/ML, and data science concepts to support evolving analytics solutions.</li><li>Data Quality &amp; Requirement Support: Validates data, supports reporting requirements, and helps ensure the accuracy and consistency of analytics solutions.</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field such as Data Science, Statistics, Computer Science, Business Analytics, or a related discipline, or equivalent practical experience.&nbsp;</li><li>Minimum of 3-4 years of relevant work experience in data analytics, reporting, or business intelligence roles.</li><li>Strong skills in analyzing data and translating reporting needs into effective analytics solutions and insights.</li><li>Very strong skills in Power BI and data visualization.</li><li>Proficiency in SQL, Excel, Power Query, and related tools such as VBA or Python for analysis, modelling, and visualization.</li><li>Working knowledge of data warehousing, data lakes, and cloud data platforms such as Snowflake or AWS.</li><li>Experience automating workflows and building low-code solutions using Power Platform tools such as Power Automate and Power Apps.</li><li>Familiarity with (predictive) analytics, AI/ML and data science.</li><li>Business understanding and financial acumen to interpret data and generate practical insights.</li><li>Comfortable working in agile ways of working, managing multiple priorities, and contributing effectively both independently and in a team environment.</li></ul>

Responsibilities: <ul><li>Engage in day-to-day support activities including incident and problem management</li><li>Perform production deployments, patch activities on the supported applications and servers.</li><li>Work with product support/development team for permanent resolution/change review – all types including enhancements, bug fixes, etc.</li><li>Work with level 1 support in application knowledge transfer in establishing standard first level recovery process/system health check monitoring/scheduled activities as well as common application user queries.</li><li>Collaborate with internal stakeholders like application, business, infrastructure, security, and operations to continuously improve the stability of applications.</li><li>Develop support operational documents to summarize common support issues.</li><li>Develop reports and drive audit RFI’s and requirements.</li><li>Develop Linux scripts based on the requirements.</li><li>Provide after office hours’ standby support and for emergency recoveries, including managing major incident of critical services.</li><li>Expected to drive improvements through influence and strong relationships with managers in other teams.</li><li>Correlate events across multiple systems to proactively surface and resolve deep, underlying issues.</li></ul> Requirements: <ul><li>Diploma/Degree in engineering/Computer Science / IT/Cyber Security from a recognized education institution</li><li>Professional qualification in information security, such as CISSP / CISM / CEH, or data Security product certifications will be advantageous.</li><li>9 to 12 years relevant experience</li><li>Strong working knowledge on Oracle Identity Governance 12c, Oracle Database, WebLogic, BI Publisher, Oracle Connectors, Linux, Unix &amp; Windows Enterprise Server OS, with mixed skills around administration, performance tuning and troubleshooting</li><li>Working knowledge of Python, java, Java Scripts,</li><li>Knowledge in network infrastructure like Load balancers, Firewalls, SSL etc</li><li>Working Knowledge on Directory - LDAP and AD Databases</li><li>Strong knowledge of Oracle SQL and proficient in writing complex SQL queries with hands on experience with reporting tools along with excellent computational ability.</li><li>Strong understanding of cybersecurity principles and frameworks including ISO 27001 &amp; NIST Cybersecurity Framework;</li></ul>

Responsibilities: Design &amp; Build/Development &amp; Support <ul><li>Develop multi-agent workflow automation patterns using Agentic AI</li><li>Process redesign and mapping to agentic workflow patterns</li><li>Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).</li><li>Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents</li><li>Profile inference latency, GPU/CPU utilization, and memory</li><li>Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions</li><li>Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents</li><li>Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.</li></ul> Operational Excellence&nbsp;<ul><li>Own on-call runbooks, SLOs, and incident reviews; embed observability</li><li>Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.&nbsp;</li></ul> Collaboration &amp; Leadership <ul><li>Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.</li><li>Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.&nbsp;</li><li>Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.&nbsp;</li></ul> Capability &amp; Technology Stack Exposure <ul><li>Experience with digital technologies in the commercial &amp; sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)&nbsp;</li></ul> Requirements: <ul><li>Minimum requirement of 2 years of building production software or data platforms.&nbsp;</li><li>Typically reflects 3 years or more with 2+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software development.&nbsp;</li></ul>

Responsibilities: <ul><li>Lead and deliver Digital Measurement Analytics for Digital Platforms in Agile methodology to drive digital data strategy that includes collection &amp; validation of data and reporting.</li><li>Partner with onsite Stakeholders and various process owners in marketing, technology and digital teams to plan and implement strategic priorities.</li><li>Present analytical results and actionable recommendations to key stakeholders on a recurring cadence, and propose innovative analytics solutions to drive business growth and enhance the customer experience.</li><li>Responsible for team’s effective communication, project deliverables, coaching team on adhering to expected timelines, accuracy &amp; compliance with meticulous project management.</li><li>Lead internal initiatives, perform other duties and/or special projects, as assigned.</li></ul> Requirements: <ul><li>Degree in Statistics, Mathematics, Economics, Engineering, or any other quantitative streams with 4+ years of hands-on relevant Analytics experience.</li><li>Minimum 6+ years of relevant work experience in lieu of specified degree.</li><li>2+ years of experience in Digital or Web Analytics Domain utilizing tools such as Adobe or Google Analytics and 2+ years of experience in SAS or SQL.</li><li>1+ years of Experience in Managing People, Coordinating work, Supervising, Evaluating performance and ensuring employees are trained.</li><li>Minimum 1+ years of experience in Data visualizations tools such as Tableau to drive insights.</li><li>Excellent oral and written communication skills with ability to collaborate, articulate and present solutions cutting across functional/agile teams in a simple yet compelling manner</li></ul>

Responsibilities: <ul><li>Designs, builds, and supports SAP platform solutions by applying sound engineering practices to ensure system stability, performance, and scalability.</li><li>Utilizes enterprise tools and methodologies to automate system deployments, transport, and administrative activities, enabling reliable and repeatable releases.</li><li>Collaborate with cross‑functional partners to translate moderately complex business and technical requirements into effective SAP Basis solutions.</li><li>Performs system validation, technical testing, monitoring, and troubleshooting to maintain the quality and availability of SAP systems.</li><li>Contributes to continuous improvement initiatives by identifying opportunities to enhance SAP Basis processes, automation, and operational efficiency.</li><li>Creates and maintains clear technical documentation for SAP landscapes, configurations, and operational procedures.</li><li>Provides technical support for moderately complex SAP Basis issues, ensuring timely resolution and minimal impact to business operations.</li><li>Drives automation and quality through the use of enterprise testing and deployment tools, including Tosca for test automation and qTest for test management, execution, and traceability.</li><li>Develops, executes, and maintains manual and automated test assets for SAP systems, ensuring end‑to‑end coverage across SIT, UAT, regression, and integration testing cycles.</li><li>Performs system validation, monitoring, defect analysis, and troubleshooting in partnership with development, security, and infrastructure teams to ensure reliability and performance.</li></ul> Requirements: <ul><li>Minimum requirement of 5 years of relevant work experience with SAP Basis.&nbsp;</li><li>Demonstrated expertise in SAP Basis engineering, with strong knowledge of SAP system architecture, technical landscape design, system administration, upgrades, transport, performance monitoring, and operational support across multiple SAP environments.</li><li>Experience managing and supporting SAP technical operations, including system availability, batch processing, interfaces, background jobs, monitoring, troubleshooting, and incident resolution in alignment with enterprise service expectations.</li><li>Proven ability to support SAP Fiori and UI technical components from a Basis perspective, including configuration, activation, performance support, and coordination with security and application teams.</li><li>Experience leveraging scripting and technical tools (such as SQL and automation utilities) to improve operational efficiency, support system analysis, and standardize SAP Basis activities.</li><li>Working knowledge of cloud‑hosted and hybrid SAP landscapes, including experience supporting SAP systems on platforms such as Microsoft Azure, AWS, or Google Cloud, with an understanding of infrastructure, connectivity, and platform operations.</li></ul>

Responsibilities: <ul><li>DATA &amp; ANALYTICAL SOLUTIONS: Oversees the development of data products and solutions using big data and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.</li><li>DATA PIPELINES: Develops and monitors streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move to data stores like data lake, data warehouse and others.</li><li>DATA SYSTEMS: Reviews existing data systems and architectures to lead identification of areas for improvement and optimization.</li><li>DATA INFRASTRUCTURE: Oversees the preparation of data infrastructure to drive the efficient storage and retrieval of data.</li><li>DATA FORMATS: Reviews and resolves appropriate data formats to improve data usability and accessibility across the organization.</li><li>STAKEHOLDER MANAGEMENT: Partners collaboratively with multi-functional data and advanced analytic teams to capture requirements and ensure that data solutions meet the functional and non-functional needs of various partners.</li><li>DATA FRAMEWORKS: Builds complex prototypes to test new concepts and provides guidance to implement data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.</li><li>AUTOMATED DEPLOYMENT PIPELINES: Oversees the development of automated deployment pipelines improving efficiency of code deployments with fit for purpose governance.</li><li>DATA MODELING: Guides the team to perform data modeling in accordance to the datastore technology to ensure sustainable performance and accessibility.</li><li>TEAM MANAGEMENT: Manages team members to achieve the organizations goals, by ensuring productivity, communicating performance expectations, creating goal alignment, giving and seeking feedback, providing coaching, measuring progress and holding people accountable, supporting employee development, recognizing achievement and lessons learned, and developing enabling conditions for talent to thrive in an inclusive team culture.</li></ul> Requirements: <ul><li>Some experience in React, including hooks, context API, and state management libraries (Redux, Zustand)</li><li>Solid experience with JavaScript (ES6+), TypeScript, HTML5, CSS3.</li><li>Strong experience with C# and .NET Framework/.NET Core.</li><li>Solid understanding of object-oriented programming.</li><li>Experience with unit testing and mocking frameworks (e.g., xUnit, NUnit, Moq).</li><li>Familiarity with design patterns (e.g., Repository, Factory, Strategy).</li><li>Experience with SQL DBs, MySQL, Postgres, or MS SQL: writing queries, stored procedures, and performancetuning.</li><li>Knowledge of RESTful APIs and message-based systems.</li><li>Experience with relational databases and data access libraries (e.g., Entity Framework, Dapper).</li><li>Knowledge of ReactJS</li><li>Proficient in Git: branching, merging, pull requests, and version control workflows.</li></ul>

Responsibilities: <ul><li>Demonstrate accountability by ensuring timely and high-quality project delivery.</li><li>Be result driven, consistently achieving measurable outcomes and meeting goals.</li><li>Act as a team player, collaborating effectively with cross-functional teams.</li><li>Exhibit a can-do mentality, tackling challenges with a proactive and positive approach.</li><li>Apply software engineering patterns and principles to design, develop, test, integrate, maintain, troubleshoot and document complex and varied software solutions and incorporate security practices in newly developed and maintained applications.</li><li>Participate in peer code review sessions to review code, coach peers and ensure code quality.</li><li>Take the lead in the assigned agile team to adopt agile philosophies, facilitate agile ceremonies and identify continuous improvement opportunities.</li><li>Incorporate the companys engineering and development best practices within the full software development lifecycle including coding standards, code reviews, source control management, building processes, testing and security principles, to deliver high quality code rapidly.</li><li>Collaborate to lead demonstration and continuous feedback sessions to improve development and help drive the long term vision.</li><li>Participate in the engineering community by maintaining and sharing relevant technical approaches and modern skills.</li><li>Independently handle complex issues with minimal supervision, while escalating only the most complex issues to appropriate staff.</li><li>Other duties as assigned</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field or equivalent experience</li><li>Confirmed experience automating pipelines for continuous integration, testing, delivery and security.</li><li>Confirmed experience architecting applications, databases, services or integrations.</li><li>Extensive experience with .NET Framework and .NET Core.</li><li>Familiarity with front-end technologies like HTML, CSS, JavaScript, and frameworks such as Angular, React, or Vue.js.</li><li>Experience with DevOps practices and tools such as Docker and CI/CD pipelines.</li><li>Knowledge of SQL Server and / or PostgreSQL for database design and management.</li><li>Hands-on experience with Kubernetes for container orchestration and management.</li><li>Experience with cloud platforms such as Azure, AWS, or GCP.</li><li>Minimum of 5 years of related work experience in software development using .NET technologies.</li></ul>

Responsibilities: <ul><li>Lead the design, development, and deployment of machine learning models using Python for applications including process optimization, predictive analytics, demand forecasting, computer vision, and decision support systems</li><li>Network across manufacturing, R&amp;D, commercial, and business functions to identify and collaboratively execute on high-impact challenges solvable through machine learning techniques</li><li>Build production-ready ML solutions within enterprise platforms (Databricks, Azure ML) including model training, endpoint deployment, and monitoring</li><li>Develop and maintain scalable, modular, well-documented code following MLOps best practices including version control, logging/metadata standards, and CI/CD principles</li><li>Lead code reviews, architectural discussions, and knowledge sharing to maintain high quality, production-ready deliverables across the team</li><li>Collaborate with domain experts and stakeholders across a wide variety of domains to understand needs, integrate ML solutions into workflows, and deliver measurable business value</li><li>Communicate complex machine learning methodology, results, and business impact clearly to technical and non-technical audiences through presentations, documentation, and visualizations</li><li>Stay current with advancements in machine learning, and apply them to solve business challenges</li><li>Mentor and provide technical guidance to data scientists, helping to grow the teams capabilities in Hyderabad</li><li>Support ML governance processes including architecture and methodology reviews, risk assessments, and compliance with enterprise standards</li><li>Lead project planning and execution, managing timelines, resources, and stakeholder expectations</li></ul> Requirements: <ul><li>Masters or Ph.D. in a relevant field such as Data Science, Statistics, Mathematics, Computer Science, Operations Research, or a domain-focused field (Engineering, Chemistry, Economics, Finance, etc.)</li><li>5-8+ years of experience in data science, machine learning, or a related field with demonstrated impact</li><li>Strong foundation in statistical and machine learning theory with proven ability to select, apply, and evaluate appropriate techniques for complex, real-world problems</li><li>Extensive hands-on experience building predictive models and deploying them to production environments using Python</li><li>Proficiency with modern ML frameworks (scikit-learn, XGBoost/CatBoost, TensorFlow/PyTorch) and data manipulation libraries (pandas, polars, numpy)</li><li>Experience with solution architecting and design for ML systems</li><li>Hands-on experience with cloud platforms such as Azure and/or Databricks for deploying and managing ML models and solutions</li><li>Experience with version control (Git), collaborative development, and code review processes</li><li>&nbsp;Strong written and oral communication skills with ability to present technical concepts and results to diverse audiences from technical teams to business leadership</li><li>History of project leadership and driving initiatives from conception to production</li><li>Strong problem-solving skills and the ability to work independently as well as lead and mentor team members&nbsp;</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust pipelines to collect, transform, and store data used in model monitoring workflows (e.g., scoring data, performance metrics, outcomes).</li><li>Build scalable data architectures to support real-time and batch monitoring, including data ingestion, enrichment, and retention practices.</li><li>Develop reusable monitoring components (e.g., performance drift detectors, threshold-based alerts, metric repositories) that support various model types and regulatory needs.</li><li>Integrate data pipelines with model lifecycle platforms, MLOps tools, and observability solutions to ensure seamless model performance tracking.</li><li>Partner with model risk and compliance teams to ensure data lineage, audit trails, and documentation are preserved and accessible for regulatory reviews (e.g., SR 11-7 compliance).</li><li>Collaborate with data scientists, model validators, and product managers to align monitoring data infrastructure with evolving model monitoring requirements.</li><li>Work closely with the model monitoring analytics and strategy monitoring analytics teams within MO&amp;A to ensure the monitoring data infrastructure adapts to changing analytics and monitoring needs. Enable visualization and reporting capabilities through dashboards (e.g., Power BI, Tableau) that summarize model health, stability, and issue alerts.</li><li>Designing and maintaining high-performance data pipelines that ingest, transform, and version datasets for Model and Strategy Monitoring</li><li>Optimize data storage and compute performance for large-scale monitoring use cases involving high-frequency scoring or model ensembles.</li></ul> Requirements: <ul><li>Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 5+ years’ experience or in lieu of degree, and 7+ years of relevant work experience in, data engineering or related roles in the financial services or regulated analytics domain.</li><li>Strong proficiency with data engineering tools and frameworks (e.g., Apache Spark, Airflow, Kafka, dbt, PySpark).</li><li>Proficient in programming languages such as SAS, Python, and SQL for building monitoring pipelines and validation checks.</li><li>Experience with cloud-based data infrastructure (e.g., AWS, Azure, GCP) and data warehousing (e.g., Snowflake, Redshift, BigQuery).</li><li>Familiarity with MLOps practices, model metadata tracking (e.g., MLflow), and monitoring toolkits (e.g., Evidently AI, Why Labs, Prometheus).</li><li>Understanding of model risk governance requirements and the role of data engineering in ensuring compliant model monitoring.</li><li>Ability to work in an agile environment and deliver high-quality, production-grade code in collaboration with DevOps and platform engineering teams.</li></ul>

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32 sql server Jobs found

Technical Delivery Manager ( Actimize ) - Comp Tech – VP2

Consultant, Data Analytics & Reporting-Food

Senior Production Support Engineer – IDM Engineering (VP2)

Software Engineer AI

AVP, Digital Analytics

SAP Basis Engineer

Manager, Data Engineering

Sr. Software Engineer - Ag & Trading .Net

Senior Data Scientist - Machine Learning

AVP – Model Ops Engineer

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Technical Delivery Manager ( Actimize ) - Comp Tech – VP2

Consultant, Data Analytics & Reporting-Food

Senior Production Support Engineer – IDM Engineering (VP2)

Software Engineer AI

AVP, Digital Analytics

SAP Basis Engineer

Manager, Data Engineering

Sr. Software Engineer - Ag & Trading .Net

Senior Data Scientist - Machine Learning

AVP – Model Ops Engineer

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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