Big Data Engineer

Top Skills - Must Haves

• big data
• Spark
• Aws
• Sql
• Python
• AI tools

Top Skills' Details

1. Big Data Engineering (Hadoop, hive, trino): core function of job - MUST have experience with petabytes of large-scale data processing and distributed systems
- Design/optimize pipelines for petabytes of data
2. Apache Spark Development & Performance Tuning
- Spark internals, troubleshooting, and optimizing for petabyte-scale workloads
3. Advanced SQL (Window functions, multi-table joins, query optimization)
4. AWS Cloud Engineering (S3, EMR, Glue, Athena, scaling clusters)
5. Python or Scala programming
6. AI/LLM Tooling & Prompt Engineering (GitHub Copilot, Q)

Secondary Skills - Nice to Haves

• ci/cd
• java
• systems troubleshooting
• Etl
• automated testing

Job Description

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
Responsibilities:
• 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 of 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.
• Ability to write and maintain automated unit, integration, and end-to-end tests
• Monitor and troubleshoot data pipelines in production environments to identify and resolve issues.

Education/Experience Requirements:
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.
Should be 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.

Additional Skills & Qualifications

Essential Technical Skills:
· AI Tool Proficiency: Hands-on experience with AI development tools (GitHub Copilot, Q Developer, ChatGPT, Claude, etc.)
· Technical Background: Strong software development background with ability to contribute to technical discussions
· Agile Methodology: Extensive experience with Scrum, Kanban, and continuous improvement practices

Big Data technologies
• Experience with Big data technologies such as Hadoop, Spark, Hive & Trino
• Evaluate understanding of common issues like:
◦ Data skew and strategies to mitigate it.
◦ Working with massive data volumes in PetaBytes.
◦ Troublehsooting job failures due to resource limitations, bad data, scalability challenged.
• Look for real-world debugging and mitigation stories.
AI Skills
· 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

Employee Value Proposition (EVP)

Candidate will architect and optimize the large‑scale data systems that fuel analytics, reporting, and AI initiatives across the organization. Your work directly enables teams to make better, faster, more strategic decisions with reliable, high‑quality data.