Data & ML Architect

Sr. Software Engineer - Ag & Trading .Net

AVP – Model Ops Engineer

Software Engineer SAP Commerce Cloud

Senior Software Engineer 1 (.Net)

Senior AI Engineer

Data Engineer

Principal HANA Database Administrator

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

Responsibilities: Strategic Leadership: <ul><li>Set the vision and direction for data and AI architecture for project and client.</li><li>Influence enterprise data and AI strategies, driving adoption of best practices in data, ML, and AI architecture.</li><li>Mentor and develop junior architects and engineers, fostering a culture of technical excellence and innovation.</li></ul> Architectural Excellence: <ul><li>Architect and design enterprise-scale data platforms and ML/AI solutions for scalability, reliability, and performance.</li><li>Define and enforce data and ML architecture standards, patterns, and governance frameworks for data pipelines, ML workflows, and analytics platforms.</li><li>Lead solution design for integrating data from diverse sources (streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services.</li></ul> AI &amp; ML Leadership: <ul><li>Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems.</li><li>Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models.</li><li>Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent data products.</li><li>Provide Ethical AI leadership to ensure intelligent solutions are implemented when required and in safe methods.</li></ul> Technical Leadership: <ul><li>Oversee data modelling (e.g. medallion architecture), data governance, and quality frameworks. Implementing technical reviews and driving high standards.</li><li>Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform.</li><li>Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps).</li></ul> Stakeholder Engagement: <ul><li>Engage with senior stakeholders to translate complex business requirements into technical solutions and strategic roadmaps.</li><li>Ensure all solutions meet security, compliance, and performance standards, and align with enterprise architecture principles.</li></ul> Innovation &amp; Emerging Technologies: <ul><li>Apply modern data and AI architecture patterns (Cloud Native, Steaming/batch ingestion, Agentic AI Design) and leverage platforms such as AI/ML, Big Data, and Data Lakehouse.</li></ul> Requirements: <ul><li>Minimum 8 years’ experience client facing roles specializing in Data and Architecture roles.</li><li>Experience in both Agile and Waterfall project environments.</li><li>Strong stakeholder management and communication skills.</li><li>Security and compliance awareness.</li><li>Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer).</li><li>Experience mentoring or managing technical teams.</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>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>

Responsibilities: <ul><li>Design, develop, and maintain scalable software solutions for the eCommerce domain.</li><li>Work as a key member of an agile Scrum team, actively participating in sprint planning, backlog refinement, daily stand-ups, and retrospectives.</li><li>Collaborating closely with development leads to align on technical direction, architecture, and implementation strategies.</li><li>Analyze and solve complex problems across the stack, from front-end interfaces to back-end services and integrations.</li><li>Understand business and technical requirements to create high-quality, maintainable deliverables.</li><li>Participate in code reviews, design discussions, and continuous improvement of engineering practices.</li><li>Ensure high standards of code quality, reliability, and system performance.</li><li>Support incident resolution and platform stability initiatives.</li></ul> Requirements: <ul><li>4+ years of hands-on programming experience in one or more languages such as Java, C#, JavaScript, Python, Spring boot etc.</li><li>Proven ability to learn and adapt quickly to new technologies, frameworks, and platforms.</li><li>Strong understanding of software engineering principles, design patterns, and scalable architecture.</li><li>Solid experience with RESTful APIs, microservices, and modern development tools (Git, CI/CD, etc.).</li><li>Strong analytical, problem-solving, and debugging skills.</li><li>Working knowledge of relational and/or NoSQL databases.</li><li>Familiarity with cloud platforms (Azure, AWS, or GCP) is a plus.</li><li>Prior experience or understanding of eCommerce systems, shopping carts, order management, product catalog, payment integration, etc., is highly desirable.</li><li>Exposure to DevOps practices, automation, and monitoring tools is a plus.</li><li>Excellent communication and collaboration skills, especially in a distributed team setting.</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust, scalable, and secure web applications.</li><li>Utilize Object-Oriented design principles and best practices to ensure high-quality software.</li><li>Write clean, efficient, and well-documented code in C# with both .NET Core and .NET Framework.</li><li>Ensure adherence to Web Standards (XML, JSON, HTML, CSS, APIs, Web Services).</li><li>Create and manage CI/CD pipelines using tools like Jenkins, GitLab CI, or Azure DevOps.</li><li>Automate repetitive tasks in the software development lifecycle, including builds, testing, and deployments.</li><li>Configure and maintain infrastructure for CI/CD pipelines, including servers and containerized environments.</li><li>Leverage cloud platforms like AWS, Azure, or GCP for scalable infrastructure and application management.</li><li>Incorporate DevOps principles to foster collaboration between development and operations teams.</li><li>Integrate unit testing frameworks (e.g., NUnit) into pipelines to ensure robust software quality.</li><li>Utilize test-driven development practices to enhance software reliability.</li><li>Work closely with developers, QA engineers, and operations teams to streamline workflows and address feedback.</li><li>Demonstrate strong communication skills to present ideas, solutions, and progress effectively.</li><li>Monitor CI/CD pipeline execution and troubleshoot issues promptly to minimize downtime.</li></ul> Requirements: <ul><li>Demonstrated knowledge of software application development (certifications and experience considered in lieu of a degree).</li><li>6+ years of experience in software development using C# and .NET.</li><li>5+ years of experience in developing .NET applications, including .NET Core and .NET Framework.</li><li>Proven experience in building enterprise-level web applications.</li><li>Strong background in Object-Oriented design and development.</li><li>Advanced JavaScript experience, including closures and prototype inheritance.</li><li>Proficiency in SQL (DDL and DML) and experience managing database structures.</li><li>Solid understanding of Web Standards (XML, JSON, HTML, CSS, APIs, Web Services).</li><li>Demonstrated use and knowledge of design patterns and cloud-native technologies.</li><li>Experience with Agile methodologies and iterative development processes.</li><li>Proficiency in CI/CD tools such as Jenkins, GitLab CI, Azure DevOps, or AWS Code Pipeline is required.</li></ul> Preferred work experience and skills: <ul><li>Strong proficiency in C#, JavaScript, and scripting languages like Bash, Python, or PowerShell for task automation.</li><li>Expertise in popular CI/CD platforms like Jenkins, GitLab CI, Azure DevOps, or AWS Code Pipeline.</li><li>Deep understanding of Git and branching strategies for effective code management.</li><li>Familiarity with unit testing frameworks like Unit, JUnit to integrate automated testing into pipelines.</li><li>Knowledge of cloud platforms like AWS, Azure, or GCP for scalable infrastructure management.</li><li>Familiarity with containerized environments (e.g., Docker, Kubernetes) and microservices architecture.</li><li>Exceptional problem-solving and analytical skills.</li><li>Strong communication and collaboration abilities.</li><li>Self-motivated and able to work independently with minimal supervision.</li><li>Detail-oriented with excellent organizational skills.</li></ul>

Role Description: <ul><li>We are building a new data engineering team to support a strategic move from legacy data estates to a modern data platform built on Databricks.</li><li>This role plays a key part in re-engineering existing systems, improving scalability, and enabling future innovation.</li></ul> Responsibilities: <ul><li>Transition legacy data systems to Databricks.</li><li>Build and maintain robust, scalable data pipelines.</li><li>Work closely with subject matter experts, product teams, and stakeholders to understand business logic.</li><li>Apply best practices in data engineering and programming.</li><li>Mentor junior engineers and contribute to knowledge sharing.</li><li>Participate in code reviews and technical discussions.</li></ul> Requirements: <ul><li>Hands-on experience in software or data engineering roles.</li><li>Strong proficiency in Python and working knowledge of PySpark.</li><li>Experience or strong interest in Databricks.</li><li>Solid understanding of SQL and structured data.</li><li>Experience with cloud platforms (AWS preferred; Azure/GCP acceptable).</li><li>Familiarity with REST APIs and event-driven architectures.</li><li>Experience using Git or similar version control systems.</li><li>Strong problem-solving skills and collaborative mindset.</li></ul> Preferred Experience <ul><li>Experience working on data platform modernization or migration projects.</li><li>Ability to refactor and improve legacy codebases.</li><li>Exposure to AI/ML data pipelines is an advantage.</li></ul> Why Join Us <ul><li>Opportunity to work on a strategic, high-impact data platform transformation.</li><li>Exposure to cutting-edge technologies including Databricks and cloud platforms.</li><li>Collaborative, inclusive team culture with strong mentorship.</li><li>Clear opportunities for career growth and skill development.</li></ul>

Role Overview: <ul><li>We are building a new data engineering team to support a strategic move from legacy data estates to a modern data platform built on Databricks.&nbsp;</li><li>This role plays a key part in re-engineering existing systems, improving scalability, and enabling future innovation.</li></ul> Responsibilities: <ul><li>Lead the transition of legacy data systems to Databricks, ensuring reliability and performance.</li><li>Design, build, and maintain robust, scalable data pipelines to support analytical and operational use cases.</li><li>Collaborate closely with subject matter experts, product teams, and business stakeholders to understand and implement business logic accurately.</li><li>Apply data engineering and programming best practices to ensure high-quality, maintainable, and secure solutions.</li><li>Mentor junior engineers, fostering technical growth and promoting knowledge sharing across the team.</li><li>Participate in code reviews, architectural discussions, and technical decision-making to uphold engineering standards.</li></ul> Requirements:&nbsp; Required Skills &amp; Experience: <ul><li>Hands-on experience in software or data engineering roles.</li><li>Strong proficiency in Python and working knowledge of PySpark.</li><li>Experience or strong interest in Databricks.</li><li>Solid understanding of SQL and structured data.</li><li>Experience with cloud platforms (AWS preferred; Azure/GCP acceptable).</li><li>Familiarity with REST APIs and event-driven architectures.</li><li>Experience using Git or similar version control systems.</li><li>Strong problem-solving skills and collaborative mindset.</li></ul> Preferred Experience: <ul><li>Experience working on data platform modernization or migration projects.</li><li>Ability to refactor and improve legacy codebases.</li><li>Exposure to AI/ML data pipelines is an advantage.</li></ul>

Role Description: <ul><li>The Principal HANA Database Administrator will serve as the organization’s top technical authority for SAP HANA database environments.</li><li>This role is responsible for designing, implementing, and optimizing large-scale HANA systems to ensure high availability, security, and performance.</li><li>The individual will lead strategic initiatives, mentor team members, and collaborate with cross-functional teams to support mission-critical enterprise applications.</li></ul> Responsibilities: Architecture &amp; Strategy <ul><li>Define enterprise-level SAP HANA architecture and standards.</li><li>Develop strategies for scalability, high availability, disaster recovery, and security compliance.</li></ul> Database Administration <ul><li>Install, configure, and upgrade SAP HANA systems.</li><li>Perform advanced performance tuning, query optimization, and memory management.</li><li>Monitor system health and proactively resolve issues.</li></ul> Data Management <ul><li>Manage data provisioning, replication, and integration with SAP and non-SAP systems.</li><li>Ensure compliance with data governance and security standards.</li></ul> Leadership <ul><li>Act as a subject matter expert for SAP HANA across the organization.</li><li>Mentor junior DBAs and provide technical guidance to project teams.</li><li>Drive automation and best practices for database operations.</li></ul> Innovation <ul><li>Evaluate emerging technologies and recommend enhancements.</li><li>Lead initiatives to improve efficiency and reduce operational risk.</li></ul> Requirements: Education: <ul><li>Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.</li></ul> Experience: <ul><li>10+ years of database administration experience, with at least 5 years in SAP HANA.</li><li>Proven track record managing large-scale, mission-critical HANA environments.</li></ul> Technical Skills: <ul><li>Expertise in SAP HANA architecture, sizing, and performance tuning.</li><li>Strong knowledge of Linux OS, virtualization, and cloud platforms (AWS, Azure, GCP).</li><li>Familiarity with SAP Basis and integration with S/4HANA, BW/4HANA.</li></ul> Certifications: <ul><li>SAP Certified Technology Specialist – SAP HANA.</li><li>Additional certifications in cloud or database technologies preferred.</li></ul>

Responsibilities: <ul><li>Lead the design and development of LLM-powered solutions for clinical summarization, intelligent chat, and document understanding to improve patient care outcomes.</li><li>Architect and implement end-to-end machine learning pipelines, including Retrieval-Augmented Generation (RAG) systems using vector databases such as Pinecone and Weaviate.</li><li>Fine-tune and optimize state-of-the-art language models (e.g., GPT, LLaMA, Mistral) and apply advanced prompt engineering to address specialty-specific healthcare use cases.</li><li>Own project delivery end to end, collaborating with stakeholders to ensure AI solutions are ethical, scalable, reliable, and well-governed.</li><li>Mentor and support junior data scientists, fostering a culture of experimentation, learning, and innovation.</li></ul> Requirements: <ul><li>Experience: 8–12 years in Data Science/ML, with at least 3+ years specifically focused on LLMs and Generative AI.&nbsp;</li><li>Technical Mastery: Deep hands-on expertise in Python and frameworks like PyTorch, Hugging Face, LangChain, or LlamaIndex.&nbsp;</li><li>Cloud Fluency: Proven ability to deploy models at scale using AWS SageMaker, Azure ML, or GCP Vertex AI.&nbsp;</li><li>MLOps Mindset: Experience with MLflow, Airflow, Docker, and Kubernetes to ensure our "bold innovations" are also stable and reliable.&nbsp;</li><li>Academic Foundation: A strong grasp of statistical analysis and evaluation techniques to mitigate hallucinations and ensure clinical accuracy.&nbsp;</li></ul>

Responsibilities: Architecture &amp; Design:&nbsp; <ul><li>Design end-to-end data architectures that integrate real-time streaming (Kafka, GCP Pub/sub) and batch processing (Big Query OR Databricks).</li></ul> Pipeline Development:&nbsp; <ul><li>Build and maintain robust ETL/ELT pipelines flowing into BigQuery/Databricks, ensuring data is clean, modeled, and ready for consumption.</li></ul> Custom Integration:&nbsp; <ul><li>Develop custom APIs and microservices using Java/Python/C# to facilitate data movement between niche systems and the data lakehouse.</li></ul> Infrastructure Management:&nbsp; <ul><li>Deploy and manage data workloads on Google Kubernetes Engine (GKE), ensuring high availability and cost-efficiency.</li></ul> Technical Leadership:&nbsp; <ul><li>Mentor junior engineers, conduct code reviews, and establish DataOps best practices (CI/CD, automated testing, and monitoring).</li></ul> Data Reliability:&nbsp; <ul><li>Implement data quality frameworks to ensure accuracy and lineage across the hybrid environment.</li></ul> Requirements: <ul><li>Experience with Terraform &amp; Azure Dev Ops (ADO).</li><li>Knowledge of workflow orchestrators like Apache Airflow (Cloud Composer).</li><li>Experience implementing Data Governance (metadata management, data cataloging).</li><li>Data Processing &amp; Storage</li><li>BigQuery: Expert-level SQL and experience with partition/cluster optimization.</li><li>Databricks: Deep knowledge of the Lakehouse architecture, Delta Lake, and Spark (PySpark/Scala) Software Engineering &amp; APIs</li><li>Languages: Proficiency in Java/Python/C# for backend development and custom data connectors.</li><li>API Design: Proven ability to build and consume RESTful APIs for data ingestion Streaming &amp; Infrastructure</li><li>Kafka/GCP Pub-Sub: Experience building event-driven architectures and managing producers/consumers.</li><li>GKE: Proficiency in containerization (Docker) and orchestrating data workloads on Kubernetes.</li></ul>

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17 gcp Jobs found

Data & ML Architect

Sr. Software Engineer - Ag & Trading .Net

AVP – Model Ops Engineer

Software Engineer SAP Commerce Cloud

Senior Software Engineer 1 (.Net)

Senior AI Engineer

Data Engineer

Principal HANA Database Administrator

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

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Data & ML Architect

Sr. Software Engineer - Ag & Trading .Net

AVP – Model Ops Engineer

Software Engineer SAP Commerce Cloud

Senior Software Engineer 1 (.Net)

Senior AI Engineer

Data Engineer

Principal HANA Database Administrator

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

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