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Data Engineer
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- Last seen on employer site
Where you can work
Hybrid
Coimbatore, Tamil Nadu, India
View location wording from the posting
Coimbatore, IN
Role overview
Extracted from the posting. Read the employer’s full description below.
- Experience working with Databricks
- Exposure to CI/CD pipelines for data engineering workflows
- Experience with workflow orchestration tools (e.g., Airflow)
What you will do
- 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
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- 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
What they are looking for
- Familiarity with AWS Cloud services (e.g., S3, Glue, EMR, Lambda, Redshift)
Employer description
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.
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