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Senior Data Infrastructure Engineer
Job Description

Why Hivel

Hivel is an AI-native engineering intelligence platform helping teams measure and improve software delivery speed, quality, and impact.

We integrate deeply with GitHub, Jira, Jenkins, GitLab, Copilot, and Cursor, turning engineering activity into real-time insights that show leaders why delivery slows down and how to move faster.

Engineering output has exploded in the AI era - but true visibility hasn’t. Hivel helps teams see beneath the surface and understand what’s really happening in their engineering systems.

Why This Role

Every company tracks what developers do - commits, PRs, and tickets. We’re building the brain that understands why things move (or don’t).

This role sits at the heart of that brain. You’ll wire up data flows from Git, Jira, and CI/CD systems to create a living graph of engineering activity - powering insights that CTOs and VPs of Engineering rely on to make better decisions, faster.

What You’ll Do

  • Build and scale multi-source data ingestion from Git, Jira, and other developer tools via APIs, webhooks, and incremental syncs.

  • Refactor and optimize Java-based ETL pipelines for modularity, reusability, and scale.

  • Design and implement parallel, event-driven processing using Kafka/SQS (batch + streaming).

  • Own Postgres optimization - schema design, partitioning, indexing, query tuning - across 100GB+ datasets.

  • Build and maintain data orchestration, lineage, and observability (Airflow, Temporal, OpenTelemetry, etc.).

  • Work with backend, product, and AI teams to make data consumable for insights and ML workflows.

  • Maintain cost-efficient, scalable infrastructure across AWS (S3, ECS, Lambda, RDS, CloudWatch).

  • Build pipelines that are self-healing, monitored, and production-grade - the kind that let you sleep through the night.

What We’re Looking For

  • 6–10 years of experience as a Backend or Data Engineer in data-heavy or analytics-driven products.

  • Deep hands-on expertise with Java and AWS (S3, ECS, RDS, Lambda, CloudWatch).

  • Proven experience fetching and transforming data from GitHub, Jira, Jenkins, Bitbucket, or similar APIs.

  • Strong fundamentals in data modeling, incremental updates, and schema evolution.

  • Expertise in Postgres performance tuning (indexing, partitioning, query optimization).

  • Experience building and scaling data pipelines handling 100M+ records in multi-tenant environments.

Brownie Points

  • Exposure to dbt, ClickHouse, Kafka, or Temporal.

  • Experience with developer analytics or productivity tools.

  • Understanding of data observability and cost optimization in modern data stacks.

  • Familiarity with AI workflows or ML data pipelines.

What You’ll Get

  • Build the data foundation for AI-driven engineering insights used by teams around the world.

  • Work directly with founders, CxOs, and senior architects on technically deep, high-impact problems.

  • See your work come alive in dashboards viewed by CTOs and CEOs.

  • Shape how thousands of engineers measure productivity in the age of AI.

  • Be part of a fast-moving, no-ego, design-driven org that values ownership, clarity, and craft.

  • Build for global markets from India

  • A culture that values ownership, speed, and growth

✨ Let’s build the nervous system of modern engineering together.

📍 Hyderabad | 💼 Full-time | 🕐 In-office

Experience: 5 to 10 years
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