Primary Responsibilities
Required Qualifications
Preferred Qualifications
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- Architect and build scalable, fault-tolerant data pipelines using Apache Spark (Java)
- Lead design of batch and streaming ETL/ELT systems handling large data volumes
- Deep-dive performance tuning: partitioning strategy, memory management, shuffle/skew optimization, job cost reduction
- Set coding standards and lead code/design reviews across the team
- Drive technical decisions on data architecture, storage formats, and pipeline orchestration
- Mentor mid-level and junior engineers; act as a technical escalation point
- Partner with product, analytics, and platform teams to translate requirements into scalable systems
- Own production reliability — on-call ownership, incident response, root‑cause analysis for pipeline failures
- Evaluate and introduce new tools/frameworks where they improve the system
- Contribute to capacity planning and cost optimization for cluster infrastructure
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- 7+ years of professional Java development experience
- 5+ years hands‑on experience with Apache Spark in production environments
- Expert‑level understanding of distributed systems: fault tolerance, data locality, shuffle mechanics, resource management
- Proven track record designing systems processing terabyte+ scale data
- Strong SQL skills and deep familiarity with columnar storage formats (Parquet, ORC, Avro, Delta Lake/Iceberg)
- Experience with cluster managers (YARN, Kubernetes) and cloud‑managed Spark
- Proficiency with Kafka
- Strong grasp of CI/CD, containerization, and infrastructure‑as‑code practices
Preferred Qualifications
- Experience with Flink or other stream‑processing frameworks
- Familiarity with data governance, lineage, and quality frameworks
- Experience with workflow orchestration at scale
- Background in system design for multi‑tenant or multi‑region data platforms
- Prior experience leading a team or acting as a technical lead
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