Data Engineer
Huemot Technology (company site, opens in a new tab)RemoteDirect career pageEst. 12–30 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Build and operate production-grade data pipelines including extraction, transformation, curation into Parquet datasets, and de-identification of personal data with rigorous testing per column.
- Own orchestration, scheduling, retries, backfills, alerting, and data-quality checks; contribute to CI/CD and infrastructure as code practices.
- Document dataset catalog and lineage; provide production support including schema drift handling and on-call duties for senior hires.
Minimum Requirements
- Proficiency in Python, SQL, and distributed processing with Apache Spark or equivalent.
- Experience building and operating batch data pipelines on AWS in production, with responsibility for pipeline failures.
- Experience with orchestration tools such as Apache Airflow, Dagster, or AWS Step Functions including incident handling outside business hours.
- Strong software engineering discipline: version control, code reviews, automated testing; ability to work from written technical standards.
- Work Experience Required: Not explicitly mentioned in the JD
Ideal Candidate Profile
- Mid-level to senior engineer, with senior candidates having mentored others and owned systems end-to-end including on-call responsibility.
- Experience working in highly regulated or sensitive data environments where data privacy and security are critical.
- Preference for candidates who have a software engineering mindset with strong opinions on idempotency, backfills, and testing derived from real production experience.