We are seeking a Data Engineer to join a client-focused engagement, with responsibilities split evenly between production support and technical/development work. This role requires 2–4 years of hands-on experience in data engineering, strong proficiency in Python, SQL, and Spark, and prior exposure to client-based project environments. The ideal candidate will be comfortable balancing operational support duties with building and optimizing data pipelines.
Job Responsibilities:
•
Provide day-to-day support (50%) for existing data pipelines, jobs, and platforms —monitoring, troubleshooting, and resolving issues to ensure smooth operations
•
Design, build, and maintain (50%) scalable data pipelines and ETL/ELT workflows using Python, SQL, and Spark
•
Collaborate with cross-functional and client teams to understand data requirements and translate them into technical solutions
•
Perform root-cause analysis on data/pipeline issues and implement fixes with minimal downtime
•
Optimize existing data workflows for performance, reliability, and cost-efficiency
•
Document processes, pipeline architecture, and support runbooks for knowledge continuity
•
Participate in on-call/support rotations as needed for the client engagement
•
Work with Databricks and/or AWS cloud environments where applicable to build or support data solutions
Basic Qualifications:
•
2–4 years of experience in a Data Engineering role
•
Strong proficiency in Python and SQL
•
Hands-on experience with Apache Spark
•
Prior experience working on client-based projects (mandatory)
•
Ability to work across both support and development responsibilities
•
Strong problem-solving and communication skills for client-facing situations
Exposure to CI/CD pipelines for data engineering workflows
•
Experience with workflow orchestration tools (e.g., Airflow)
Benefits
We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.