Role: Lead Data Engineer

Location: Chennai (Work from Office)

Experience: 8 - 12 years

About the Role:

We are looking for an experienced Lead Data Engineer to drive the design, development, and management of our data infrastructure while leading a team of 4 engineers. This role combines strong hands-on technical expertise with people management and delivery ownership and requires someone comfortable using modern AI-assisted ("vibe coding") tools to rapidly build and ship data products, while maintaining the infrastructure that powers them.

Key Responsibilities:

Technical Leadership & Development:

- Architect, build, and optimize scalable data pipelines using Databricks, PySpark, and Python.

- Write and review complex SQL queries for data transformation, validation, and performance tuning.

- Design and maintain data models and ETL/ELT workflows across Databricks environments.

- Support or lead development of ML models/pipelines for data products (feature engineering, model training, deployment, and monitoring).

- Build data product applications using AI-assisted "vibe coding" tools (Claude Code, Cursor, or similar) to rapidly prototype, develop, and ship internal tools, dashboards, and data-driven applications.

- Establish and enforce best practices for code quality, version control, and CI/CD using Git.

- Champion the adoption of AI-assisted development tools across the team to improve developer velocity, code review efficiency, and documentation.

- Conduct code reviews, architecture reviews, and technical design sessions.

Infrastructure & Platform Ownership:

- Own and maintain the infrastructure underlying data products including compute clusters, transactional databases, job orchestration, environments, deployment pipelines, and monitoring.

- Ensure data pipeline reliability, observability, and cost optimization across Databricks.

- Manage access controls, environment configuration, and platform scaling for data product apps.

- Troubleshoot infrastructure issues end-to-end (compute, storage, networking, connectivity).

Team & People Management:

- Lead, mentor, and grow a team of 4 engineers, providing technical guidance and career development support.

- Conduct 1:1s, performance reviews, and skill-development planning for team members.

- Foster a culture of continuous learning and rapid upskilling in response to evolving tech/business needs.

- Encourage and enable the team to adopt new tools and frameworks quickly.

Delivery & Process Management:

- Own sprint planning, backlog grooming, and sprint retrospectives for the team (Agile/Scrum).

- Break down business requirements into well-scoped technical tasks and user stories.

- Track sprint velocity, manage blockers, and ensure timely delivery of data engineering initiatives.

- Coordinate with cross-functional stakeholders (analytics, product, business teams) to align priorities.

Required Skills & Experience:

- 8+ years of experience in data engineering, with at least 2+ years in a technical leadership or team lead role.

- Strong hands-on expertise in Databricks (notebooks, clusters, job orchestration, Delta Lake).

- Proficiency in PySpark and Python for large-scale data processing.

- Advanced SQL skills (query optimization, stored procedures, performance tuning).

- Experience with Microsoft SQL Server (T-SQL, database design, troubleshooting).

- Experience with OCR data extraction (Azure Document Intelligence, AWS Textract).

- Solid understanding of Git workflows (branching strategies, PR reviews, merge conflict resolution).

- Hands-on experience building applications using AI coding tools / vibe coding (Claude Code, Cursor, GitHub Copilot, or similar).

- Experience maintaining and troubleshooting infrastructure supporting data products (compute, orchestration, deployment).

- Working knowledge of Machine Learning concepts and lifecycle (model training, deployment, monitoring).

- Proven experience running Agile sprint planning, backlog management, and team ceremonies.

- Experience managing and mentoring a small engineering team (3-5 members).

- Demonstrated ability to quickly learn and adopt new technologies in response to business needs.

Preferred Qualifications:

- Experience with cloud platforms (Azure preferred, Databricks stack).

- Familiarity with CI/CD pipelines (Azure DevOps, GitHub Actions, etc.).

- Experience with data governance frameworks and data quality tools.

- Bachelor's/Master's degree in Computer Science, Engineering, or related field.

Soft Skills:

- Strong communication skills to bridge technical and non-technical stakeholders.

- Ability to balance hands-on coding with people management responsibilities.

- High adaptability - comfortable navigating ambiguity and fast-changing tech/business priorities.

- Problem-solving mindset with a focus on scalable, maintainable solutions.