Senior Java Consultant

Job Description

Essential Job Functions

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Designs, develops, tests, and maintains features and services that ingest multiple data sources and surface insights through correlation and analysis, delivering clean, maintainable, well-tested code.

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Takes ownership of moderately complex components end to end — from design through delivery and support — with limited guidance.

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Participates in architecture and design discussions, contributes technical input, and helps shape solutions for the team.

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Identifies and resolves technical issues and dependencies, escalating broader risks appropriately to keep work on track.

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Supports production systems, troubleshoots issues, and improves reliability, performance, and maintainability of existing code and infrastructure.

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Participates in code reviews — submitting own work and providing constructive feedback — and helps apply and improve the team's coding standards, tools, and best practices.

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Provides informal guidance to junior engineers and contributes to onboarding and knowledge sharing.

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Applies computer science fundamentals — algorithm design, problem solving, complexity analysis, and data structures — and growing experience with Big Data technologies to solve business problems.

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Uses AI-assisted development tools to work more effectively, applying good judgment to review generated output for correctness, security, and quality.

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Builds productive working relationships across the team, communicates progress and blockers proactively, disagrees and commits when needed, and demonstrates FINRA's values through in-person and virtual collaboration in furtherance of FINRA's mission of investor protection and market integrity.

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Required Technical Skills

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Proficiency in Java, Python, and/or Node.js, with solid object-oriented development and RESTful API design; familiarity with microservices architecture.

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Working experience with Big Data processing frameworks such as Apache Spark, EMR (Presto, Trino), and Athena.

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Experience building ETL/ELT pipelines for data ingestion, transformation, and loading, including batch and (ideally) streaming processing.

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Understanding of data lake and data warehouse patterns — partitioning, schema management, and file formats (Parquet, ORC, Avro) — with SQL performance tuning for analytical workloads.

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Exposure to workflow orchestration and scheduling (AWS Glue, Step Functions, Airflow) and to data quality, validation, and pipeline monitoring.

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Relational databases (PostgreSQL, MySQL, Aurora) and working knowledge of NoSQL databases (DynamoDB, MongoDB, Cassandra).

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Core AWS services (EC2, S3, Lambda, RDS, ECS, API Gateway), CloudWatch/CloudTrail, IAM, and basic VPC networking; exposure to Infrastructure as Code (Terraform/CloudFormation).

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CI/CD pipelines, test automation and unit testing, and software security best practices.

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Nice to Have

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QuickSight for dashboards and data visualization.

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Frontend applications (React, Angular).

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GitLab CI/CD exposure.

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AI development tools (e.g., Amazon Q or similar code assistants), with the ability to validate generated code for correctness, quality, and security, and good judgment about when human review is required.

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Education/Experience Requirements

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Bachelor's degree in Computer Science, Information Systems, or a related discipline with at least five (5) years of related experience, or the equivalent combination of education and work experience. Requires solid experience in object-oriented development, cloud technologies, and data storage technologies (both relational and NoSQL), along with growing experience in system design, performance tuning and optimization, DevOps and CI/CD, test automation and unit testing, and software security.

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# LI-CGTS

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# TS-2505