SDE IV (ML Engineering)
InMobi (company site, opens in a new tab)7–10 yrsLucknowOn-siteDirect career pageEst. 28–48 LPA
Posted on 16 Sept
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Job description
Structured overview of role & requirements
About This Role
- Architect and develop a self-serve data platform-as-a-product integrating OSS tools, proprietary services, and cloud/SaaS infrastructure.
- Operate and scale distributed systems processing petabytes of data daily on multi-region Kubernetes infrastructure ensuring elasticity and fault tolerance.
- Optimize performance and ensure observability and data quality for large scale batch and real-time streaming data workflows with automated SLA enforcement.
Minimum Requirements
- 7–10 years experience building, optimizing, and operating production data platforms.
- Strong expertise in data engineering fundamentals including data modeling, partitioning, query optimization, and data lake architecture (Iceberg, Polaris catalog).
- Hands-on experience with distributed compute frameworks Spark (PySpark/Scala), Flink streaming, orchestration with Airflow, data transformation with DBT, and data quality validation frameworks.
- Proficiency in Kubernetes platform development, cloud infrastructure (GKE multi-region clusters, GCS), programming (Python, PySpark, Scala), and IaC (Terraform, Helm, GitOps).
Ideal Candidate Profile
- Experienced senior engineer comfortable bridging open-source tools and proprietary cloud services into unified production-grade data platform infrastructure.
- Demonstrated ability to operate large-scale distributed data systems with multi-region Kubernetes and autoscaling.
- Skilled in integrating telemetry and observability frameworks and enforcing data SLAs/SLOs with automated incident management for 24/7 platform uptime.