Staff/Lead Data Engineer- AI Developer Productivity

4 weeks ago

Chennai, Tamil Nadu, India C4Scale Full time
Location: Chennai / Bengaluru, India (100% Work from Office)

About Us:

Join our innovative team working on cutting-edge GenAI products that are shaping the future of technology. We offer an exciting environment where you'll work end-to-end software, build on the cloud, be groomed with AI expertise.

What You'll Do-

- Own the end‑to‑end analytics platform that quantifies how AI assistants and agentic tooling impact engineers from instrumentation to insight.
- Build batch & real‑time pipelines with Airflow/DBT, Kafka / Flink, ensuring
- Ingest and stream events at scale using Kafka and Confluent Cloud; land raw data in Snowflake via Python‑based ELT and dbt.
- Design and implement telemetry in IDE extensions, CLIs and GitHub workflows (TypeScript/JavaScript plug‑ins & SDKs) to capture rich, privacy‑safe events.
- Model canonical tables that power dashboards and experimentation.
- Collaborate with Developer Experience, Platform and Data Science teams to turn hypotheses into metrics and metrics into product decisions.
- Establish code standards & CI/CD for s/w engineering in Python and SQL (dbt tests, data contracts).
- Coach and mentor a growing team of analytics and software engineers.
- Continuously improve observability of the data platform (OpenTelemetry, Datadog) and drive cost/performance tuning in Snowflake.
- Develop experimentation frameworks that link AI‑tool usage to outcomes such as PR cycle time, defect density and on‑call load.

What you'll need (Qualifications)-

- 8+ years building data or analytics platforms; 2+ years in a Staff/Lead capacity shipping production systems.
- Expertise in Python (asyncio, pandas, PySpark) and SQL; fluency with modern data‑stack tooling (dbt, Snowflake, DuckDB).
- Hands‑on Kafka (topics, schema registry, ksqlDB/Flink) and event‑driven design patterns;
- Strong JavaScript/TypeScript skills for developing IDE or browser plug‑ins, GitHub Apps, and internal SDKs.
- Proven pipeline orchestration with Airflow or relevant tech; familiarity with infra‑as‑code (Terraform, Helm or other IAC) and container runtimes (K8s or ECS).
- Experience collaborating with ML/AI teams; comfortable analysing LLM or code‑gen usage patterns.
- Security & compliance mindset for sensitive code and developer data;
- Excellent communication skills - able to translate data insights into actionable product and engineering decisions for senior leadership.

Nice to have-

- Using Coding tools like Claude, Copilot, Cursor or similar AI coding assistants.
- Experience visualising developer metrics in Looker or Hex.
- Contributions to open‑source data tools or technical blogging on analytics engineering.

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