Senior Data Engineer
Sumo Logic (company site, opens in a new tab)5+ yrsNoidaOn-siteDirect career pageEst. 20–32 LPA
Posted 2h ago
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Job description
Structured overview of role & requirements
About This Role
- Own scalable Databricks pipelines and reusable ingestion frameworks for onboarding enterprise applications, APIs, databases, and other data sources.
- Deliver reliable, analytics-ready Bronze/Silver/Gold datasets, including batch and near-real-time ingestion, governance, and performance and cost optimization.
- Maintain existing Redshift and EC2 workflows; partner with Analytics, Engineering, IT/Cloud, Security, and business stakeholders on production data solutions.
Minimum Requirements
- Work Experience Required: 5+ years in data engineering or a related technical role, including developing and supporting production data pipelines.
- Strong hands-on expertise in Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake; experience optimizing production workloads.
- Experience with data ingestion and enterprise integrations, medallion architecture, orchestration, and reliable processing patterns such as retries, schema evolution, backfills, and recovery.
- Working knowledge of AWS, especially IAM, S3, and secure connectivity; experience with Git/GitHub, code reviews, automated testing, and CI/CD. Role location: Noida (Hybrid).
Ideal Candidate Profile
- Has built and operated production-grade Databricks platforms, with strong practical judgment around pipeline reliability, incremental processing, and compute efficiency.
- Particularly relevant experience includes Auto Loader, Lakeflow Spark Declarative Pipelines, advanced incremental ingestion, and Unity Catalog governance.
- Can maintain cloud-connected data workflows and translate stakeholder needs into governed, documented datasets; the role also includes providing technical guidance to team members.