5+ yrsOn-siteDirect career pageEst. 12–22 LPA
Posted 26d ago
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Job description
Structured overview of role & requirements
About This Role
- Build and maintain batch and streaming data pipelines from source systems to curated datasets used by analysts, data scientists, and application teams.
- Own pipeline reliability including monitoring, on-call incident response, root cause analysis, and performance tuning with explicit cost considerations.
- Design schemas and data models for analytics; implement data quality checks and compliance controls; maintain documentation including data dictionaries and lineage.
Minimum Requirements
- 5+ years of experience building production data pipelines.
- Proficient in Python development for data engineering with testing and CI/CD experience.
- Strong SQL and PySpark skills including performance tuning and troubleshooting.
- Hands-on experience with Azure data platform components: Data Factory, Databricks, Synapse/Fabric, and ADLS.
Ideal Candidate Profile
- Experienced in data modeling fundamentals such as normalization, star schemas, and slowly changing dimensions, comfortable balancing query performance and maintainability.
- Demonstrates engineering discipline with version control, code review, automated testing, and infrastructure as code practices.
- Consultative approach with customers in technical environments; capable of translating complex pipeline issues to non-technical stakeholders for impact analysis.