The Role
Build, maintain, and troubleshoot data pipelines and workflows using Python, SQL, and Spark. Provide production and client-facing technical support, collaborate with teams to resolve issues, and optimize data engineering solutions.
Summary Generated by Built In
Position Overview:
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
Preferred Skills:
- Experience working with Databricks
- Familiarity with AWS Cloud services (e.g., S3, Glue, EMR, Lambda, Redshift)
- Exposure to CI/CD pipelines for data engineering workflows
- Experience with workflow orchestration tools (e.g., Airflow)
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.
Skills Required
- 2-4 years of relevant Data Engineering experience
- Strong hands-on experience with Python
- Strong hands-on experience with SQL
- Strong hands-on experience with Spark
- Prior experience working on client-based projects
- Experience in production support for data pipelines
- Experience with Databricks
- Exposure to AWS Cloud
- Strong troubleshooting and problem-solving skills
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The Company
What We Do
We provide customized data and analytics consulting services, including automation and software development for a sustainable and intuitive digital transformation.
