Surface DNI - Data Engineer
Chevron Corporation (company site, opens in a new tab)5–8 yrsBengaluruOn-siteDirect career pageEst. 20–30 LPA
Posted 8h ago
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Job description
Structured overview of role & requirements
About This Role
- Build and maintain automated Azure-based data pipelines and ETL processes, using cloud storage and compute services to deliver data solutions.
- Own pipeline performance, scalability, reliability, data validation, monitoring, troubleshooting, documentation, and CI/CD deployment.
- Translate data needs from analysts, scientists, architects, and other stakeholders into dependable data solutions.
Minimum Requirements
- Work Experience Required: JD gives two ranges—5–7 years demonstrating high proficiency in programming fundamentals, and 2–8 years as a Data Engineer or similar role involving data and ETL processes.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- Strong Azure data-service knowledge (including Data Factory, Synapse, Databricks, Blob Storage, and ADLS Gen2); efficient SQL DML for modern relational databases; software engineering practices such as CI/CD, version control, and testing; and experience with big data technologies such as Spark.
- Chevron states it cannot sponsor employment visas or consider applicants on time-limited visa status.
Ideal Candidate Profile
- Has hands-on experience delivering production data pipelines across Azure storage and compute services, with attention to performance, reliability, and data quality.
- Can apply software engineering practices to data solutions, including deployment automation, testing, version control, and operational troubleshooting.
- May be a stronger match with Python or PySpark experience, plus exposure to formats such as Parquet, Delta, or Avro, API data sources, Azure DevOps, or Ansible; these are preferred rather than stated minimums.