AVP, Principal Software Engineer (Senior Technical lead)

Senior App Developer – Java, Production Engineering

Principal Platform Engineering – Digital Integration

Senior Machine Learning Engineer (Production & MLOps Focus)

Java Backend Engineer

Data Engineer / Senior / Supervisor

Responsibilities: <ul><li>Lead the development effort for cloud-native applications across the Caching Solutions and Rewards System teams, ensuring timely execution against committed business outcomes.</li><li>Drive business commitments by aligning scope, sequencing, and technical approach with Product Management, and ensuring delivery plans are realistic, transparent, and measurable.</li><li>Design and implement continuous integration and continuous delivery (CI/CD) processes to deliver applications to production, fostering a culture of continuous process improvement.</li><li>Provide hands-on technical leadership through architecture/design reviews, code reviews, and guidance to engineers to ensure compliance with standards and best practices.</li><li>Perform Technology Alternate Assessments and create Proofs-of-Concept (as necessary) to validate options and inform technical decisions.</li><li>Work collaboratively with Product Management and Platform Engineering teams during development, launch, and continuing refinement of products iteratively.</li><li>Collaborate with internal technical resources and third-party vendors to resolve issues, understand</li><li>underlying causes, and implement sustainable solutions.</li><li>Work with team members to design, architect, and implement solutions across geographic locations, ensuring effective coordination and consistent engineering execution.</li><li>Coordinate and communicate status across stakeholders, and report delivery progress, risks, and dependency needs to leadership on a regular cadence.</li><li>Maintain deep hands-on technical knowledge by evaluating trends in modern software development practices; continuously learn and stay at the leading edge of industry trends.</li></ul> Requirements: <ul><li>Bachelor’s Degree with 8+ years of system engineering experience, or in lieu of a degree 10+ years of skilled system engineering experience.</li><li>8+ years of Strong hands-on development experience in Java and Spring Boot for building enterprise-grade services.</li><li>5+ years of Proven expertise in designing and implementing cloud-native applications using a microservices-based architecture.</li><li>Solid knowledge of event streaming and processing patterns using Kafka.</li><li>Experience deploying and operating applications on cloud platforms such as AWS and PCF (Pivotal Cloud Foundry).</li><li>Strong understanding of data storage and caching concepts and implementations using GemFire, Redis &amp; Elastic cache.</li><li>5+ years of Working knowledge of database design and persistence using MySQL, Aurora SQL &amp; no SQL.</li><li>Experience with observability, logging, and production monitoring, including tools such as Splunk and New Relic</li></ul>

Responsibilities: <ul><li>Own runtime health and operational stability of production services.</li><li>Participate in on-call support rotations.</li><li>Investigate production incidents and implement permanent fixes.</li><li>Develop automation for monitoring, alerting, deployments, and incident remediation.</li><li>Improve system reliability, scalability, and performance.</li><li>Perform capacity planning and performance tuning.</li><li>Support Couchbase and PostgreSQL databases.</li><li>Leverage AI tools to improve engineering productivity and operational efficiency.</li><li>Rotate between SRE and feature engineering teams based on business priorities.</li></ul> Requirements: <ul><li>8+ years of backend software engineering experience.</li><li>Strong Java programming skills.</li><li>Experience with REST APIs and microservices.</li><li>Experience with messaging platforms (AMQ, MQ, Kafka).</li><li>Azure or GCP cloud experience.</li><li>Strong debugging and production troubleshooting skills.</li><li>Experience with Couchbase and PostgreSQL.</li><li>Knowledge of monitoring and logging platforms.</li></ul>

Responsibilities: <ul><li>Technical Leadership &amp; Strategy: Create long-term Integration Strategy and Roadmap, Define and implement Integration patterns &amp; standards</li><li>Technology Evaluation: Research, evaluate, and adopt emerging technologies, tools, and industry trends to enhance integration capabilities</li><li>Solution Architecture: Design scalable and reusable middleware components, including API gateways, message brokers, iPaas and application servers</li><li>Infrastructure Management: Deploy, manage and monitor integration solutions to ensure high availability, optimal performance and minimal downtime</li><li>Governance &amp; Standards: Establish and enforce best practices, security measures, and documentation standards for middleware platforms</li><li>Collaboration &amp; Leadership: Ability to work across teams, mentor engineers, and communicate technical strategies to stakeholders.</li><li>Experience: Substantial experience in multiple middleware technologies for architecture design, software development and system administration in both cloud-native and hybrid environments</li><li>Systems Thinking: Ability to evaluate, design and maintain future ready, secure, scalable digital integration solutions.</li></ul> Requirements: <ul><li>Minimum requirement of 8 years of relevant work experience. Typically reflects 12 years or more of relevant experience.</li><li>Technical Expertise: Strong proficiency with middleware technologies such as</li><li>Integration Platforms: Boomi, SAP BTP, MuleSoft</li><li>API Gateways: Kong, Layer7, Apigee</li><li>B2B/EDI: Open Text, Boomi, IBM Sterling</li><li>Messaging Queue: Kafka, Solace, Pulsar</li><li>Web/App Servers: WebLogic, WebSphere, Tomcat</li><li>Technical Services: Jira, GitHub, Azure DevOps, Datadog, AppDynamics</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: <ul><li>Collaborate with team, high availability, concurrent and fault tolerant software systems.</li><li>Significantly contribute to development of Aladdin’s global, multi-asset trading platform.</li><li>Work with product management and business users to define the roadmap for the product.</li><li>Design and develop innovative solutions to complex problems, identifying issues and roadblocks.</li><li>Apply validated quality software engineering practices through all phases of development.</li><li>Ensure resilience and stability through quality code reviews, unit, regression and user acceptance testing, dev ops and level two production support.</li><li>Be a leader with vision and a partner in brainstorming solutions for team productivity, efficiency, guiding and motivating others.</li><li>Drive a strong culture by bringing principles of inclusion and diversity to the team and setting the tone through specific recruiting, management actions and employee engagement.</li><li>For VP Level: In addition to above, a VP level candidate should be able to lead individual projects priorities, deadlines and deliverables using AGILE methodologies.</li></ul> Requirements: Qualifications: <ul><li>B.S. / M.S. degree in Computer Science, Engineering, or a related subject area</li><li>For VP Level: 8+ years of proven experience</li><li>For Associate Level: 4+ years of experience</li></ul> Skills and Experience: <ul><li>A proven foundation in core Java and related technologies, with OO skills and design patterns</li><li>Track record building high quality software with design-focused and test-driven approaches</li><li>Good hands-on object-oriented programming knowledge in Java, Spring, TypeScript, JavaScript, Microservices, Angular (2.0+), React.</li><li>Strong knowledge of Open-Source technology stack (Spring, Hibernate, Maven, JUnit, etc.).</li><li>Experience with relational database and/or NoSQL Database (e.g., Apache Cassandra)</li><li>Great analytical, problem-solving and communication skills</li><li>Some experience or a real interest in finance, investment processes, and/or an ability to translate business problems into technical solutions.</li><li>For VP Level: In addition to the above, a VP level candidate should have experience leading development teams, projects or being responsible for the design and technical quality of a significant application, system, or component. Ability to form positive relationships with partnering teams, sponsors, and user groups.</li></ul> Nice to have and opportunities to learn: <ul><li>Exposure to building microservices and APIs ideally with REST, Kafka or gRPC.</li><li>Experience working in an agile development team or on open-source development projects.</li><li>Experience with optimization, algorithms or related quantitative processes.</li><li>Exposure to high scale distributed technology like Kafka, Mongo, Ignite, Redis</li><li>Experience with Cloud platforms like Microsoft Azure, AWS, Google Cloud</li><li>Experience with DevOps and tools like Azure DevOps</li><li>Experience with AI-related projects/products or experience working in an AI research environment.</li><li>A degree, certifications or opensource track record that shows you have a mastery of software engineering principles.</li></ul>

Role Description:The Data Engineering Senior Supervisor will lead a small team of data engineering professionals to design, build and operate high performance data centric products or solutions through the use of modern engineering practices and technologies.In this role, you will provide guidance to ensure the delivered data centric products or solutions are scalable, sustainable and robust.You will also lead team development and cross team relationships and delivery to advance the company's engineering delivery.Responsibilities:Lead a local or regional team of engineering professionals that design, develop, deploy and enhance new and existing data centric products or solutions through the use of modern platforms and technologies.Provide routine inputs and guidance to the data engineering team on business requirements analysis, technical specification's preparation, product delivery, testing and operation to support businesses strategic direction.Coach engineers, share relevant technical approaches, identify new trends, modern skills and present new methodologies within the data engineering community.Lead and develop a team, coach and make decisions related to talent management, hiring, performance, and disciplinary actions.Other duties as assignedRequirements:Minimum QualificationsBachelor's degree in a related field or equivalent experience.Minimum of four years of related work experience.Minimum of two years leading a team of Data Engineers.Preferred QualificationsConfirmed data engineering experience with data storage and management of large, heterogenous datasets, including formats, structures, and cataloging with such tools as Iceberg, Parquet, Avro, ORC, S3, HFDS, HIVE, Kudu or others.Experience leading Big Data engineering teams working in environments such as Hadoop and SparkExperience leading technology strategies with cloud Platforms including AWS, GCP or AzureExperience leading engineering teams working in streaming and stream integration or middleware platforms, tools, and architectures such as Kafka, Flink, JMS, or Kinesis.Confirmed knowledge of best practice patterns and how to apply them to modern data architectures, including data warehouses, data lakes, data mesh, hubs and associated capabilities including ingestion, governance, modeling, observability and more.Experience leveraging transformation and modeling tools, including SQL based transformation frameworks, orchestration and quality frameworks including dbt, Apache Nifi, Talend, AWS Glue, Airflow, Dagster, Great Expectations, Oozie and others.Strong programming knowledge of SQL, Python, R, Java, Scala or equivalent.Proficiency in engineering tooling including docker, git, and container orchestration services.Strong experience leading devops teams with demonstratable understanding of associated best practices for code management, continuous integration, and deployment strategies.Experience and knowledge of data governance considerations including quality, privacy, security associated implications for data product development and consumption.A passion for quality and continuous improvement with an owners mindset.Ability to work effectively as part of a team, group and cultureAbility to navigate ambiguity and work in agile ways.

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6 kafka Jobs found

AVP, Principal Software Engineer (Senior Technical lead)

Senior App Developer – Java, Production Engineering

Principal Platform Engineering – Digital Integration

Senior Machine Learning Engineer (Production & MLOps Focus)

Java Backend Engineer

Data Engineer / Senior / Supervisor

WhiteCrow
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AVP, Principal Software Engineer (Senior Technical lead)

Senior App Developer – Java, Production Engineering

Principal Platform Engineering – Digital Integration

Senior Machine Learning Engineer (Production & MLOps Focus)

Java Backend Engineer

Data Engineer / Senior / Supervisor

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

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