Big Data Consultant

We are seeking a highly skilled and experienced Big Data Engineer to design, develop, and optimize large-scale data processing systems. In this role, you will work closely with cross‑functional teams to architect data pipelines, implement data integration solutions, and ensure the performance, scalability, and reliability of big data platforms. The ideal candidate will have deep expertise in distributed systems, cloud platforms, and modern big data technologies such as Hadoop, Spark etc.

• Design, develop, and maintain large‑scale data processing pipelines using Big Data technologies (e.g., Hadoop, Spark, Python, Scala).
• Implement data ingestion, storage, transformation, and analysis solutions that are scalable, efficient, and reliable.
• Stay current with industry trends and emerging Big Data technologies to continuously improve the data architecture.
• Collaborate with cross‑functional teams to understand business requirements and translate them into technical solutions.
• Optimize and enhance existing data pipelines for performance, scalability, and reliability.
• Develop automated testing frameworks and implement continuous testing for data quality assurance.
• Conduct unit, integration, and system testing to ensure the robustness and accuracy of data pipelines.
• Work with data scientists and analysts to support data‑driven decision‑making across the organization.
• Write and maintain automated unit, integration, and end‑to‑end tests.
• Monitor and troubleshoot data pipelines in production environments to identify and resolve issues.

• Minimum Bachelor’s degree in Computer Science, Information Systems or related discipline with at least five (5) years of related experience, or equivalent training and/or work experience.
• Master’s degree and past Financial Services industry experience preferred.
• Demonstrated technical expertise in object‑oriented and database technologies/concepts which resulted in deployment of enterprise‑quality solutions.
• Past experience with developing enterprise‑quality solutions in an iterative or Agile environment.
• Extensive knowledge of industry‑leading software engineering approaches including Test Automation, Build Automation and Configuration Management frameworks.
• Strong written and verbal technical communication skills.
• Demonstrated ability to develop effective working relationships that improved the quality of work products.
• Well‑organized, thorough, and able to handle competing priorities.
• Ability to maintain focus and develop proficiency in new skills rapidly.
• Ability to work in a fast‑paced environment.
• Experience with object‑oriented programming languages such as Java, Scala or Python.

• AI Tool Proficiency:
  Hands‑on experience with AI development tools (Git Hub Copilot, Q Developer, ChatGPT, Claude, etc.)
• Strong software development background with ability to contribute to technical discussions.
• Extensive experience with Scrum, Kanban, and continuous improvement practices.
• Experience with Big Data technologies such as Hadoop, Spark, Hive & Trino.
• Understanding of common issues such as data skew and strategies to mitigate it; handling massive data volumes in petabytes; troubleshooting job failures due to resource limitations, bad data, or scalability challenges.
• Real‑world debugging and mitigation stories.
• Prompt Engineering:
  Proficiency in crafting effective prompts for AI coding assistants and analysis tools.
• AI Workflow Design:
  Experience redesigning development processes to leverage AI capabilities.
• Data Analysis:
  Ability to interpret AI‑generated insights and translate them into actionable team improvements.
• Change Management:
  Experience leading teams through AI adoption and workflow transformation.
• SQL skills: comfort with SQL window functions, multi‑table joins, aggregations, and handling edge cases such as NULLs, duplicates, ordering.
• Knows Spark’s core architecture (executors, tasks, stages, DAG) and performance tuning techniques (partitioning, caching, broadcast joins, etc.).
• Experience with AWS services such as S3, EMR, Glue, Lambda, Athena, and EKS or serverless knowledge.
• Programming in Python or Scala: clean, modular, and performant code; functional programming concepts; collections, concurrency, and memory management.
• Experience managing production data pipelines/ETL systems.

• Experience with managing production data pipelines/ETL systems.