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Lead Data Engineer

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Onsite

Lead Data Engineer

Synergy Maritime

Lead Data Engineer

Skills

SQL QueriesData EngineeringData MiningPythonMicrosoft SQL ServerDatabricksGitData AnalysisMachine LearningAIAWSGitHubPySparkAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Chennai, Tamil Nadu, India

Work mode:

Onsite

Published on:

20 August 2026

What they need


Role: Lead Data Engineer

Location: Chennai (Work from Office)

Experience: 8 to 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 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

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