Team Lead, Data Platform

Responsibilities

• Lead and grow a team of approximately 5 software engineers in India, providing technical direction and hands-on contribution.
• Own the technical vision and roadmap for the Data Intelligence Hub (DIH) data platform in India.
• Design and evolve scalable, data-centric backend services and pipelines to support Digital Twin and AI/agentic use cases.
• Define and enforce data modeling standards (e.g., Bronze/Silver/Gold layers) across DIH systems.
• Build end-to-end, idempotent, and resilient data pipelines from raw industrial events to validated datasets.
• Make key architectural decisions regarding storage, lakehouse, and streaming systems (e.g., Databricks, Kafka).
• Partner with AI/ML teams to ensure data models and pipelines are agent-ready and tool-friendly.
• Hire, onboard, and coach engineers on system design, testing, and production ownership.

Requirements

• 8+ years of software engineering experience building backend or data-intensive systems in production.
• 3+ years in a Tech Lead or Team Lead role, including design ownership and technical mentorship.
• Strong Python engineering skills with experience in production-grade system design.
• Deep SQL and data modeling expertise, including schema design and event-time systems.
• Experience building incremental, idempotent pipelines that handle duplicates, late data, and backfills.
• Experience with cloud platforms and the modern data stack (e.g., AWS/GCP/Azure, Databricks, Spark, Kafka, BigQuery).
• Proven ability to operate and debug production systems (metrics, logging, tracing, and data quality).
• Strong communication skills for collaborating with distributed international teams.

Preferred Qualifications

• Experience with Industrial IoT, digital twins, or knowledge graphs.
• Experience with AI/LLM systems, including RAG, agents, and tool use.
• Experience building new engineering teams or charters in India or globally.

About the Company

Augury is a leader in Machine Health and Process Health solutions. We use purpose-built AI technology to provide manufacturers with insights into the health of machines and operations, helping them eliminate downtime, reduce waste, and achieve sustainable production.