Data Engineer
ShyftLabs · Hybrid
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Job details
- Work model
- Hybrid
- Salary
- Not listed by source
- Location
- Coimbatore
- Occupation
- Database Architects(O*NET 15-1243.00)
What the role asks for
What they're asking for
- 2–4 years of experience in a Data Engineering roleExperience
- Strong proficiency in Python and SQLSkill
- Hands-on experience with Apache SparkSkill
- Prior experience working on client-based projects (mandatory)Skill
- Ability to work across both support and development responsibilitiesSkill
- Strong problem-solving and communication skills for client-facing situationsSkill
- Experience working with DatabricksSkillPreferred
- Familiarity with AWS Cloud services (e.g., S3, Glue, EMR, Lambda, Redshift)SkillPreferred
- Exposure to CI/CD pipelines for data engineering workflowsSkillPreferred
- Experience with workflow orchestration tools (e.g., Airflow)SkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job 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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