Lead Data Engineer

AnalytixHub.ai helps organizations move from talking about data to delivering measurable business outcomes. The company bridges the gap between data consulting and engineering execution by designing and operationalizing Data & AI ecosystems that drive real impact. Our work spans data strategy, predictive modeling, and intelligent dashboards, with a clear focus on efficiency, growth, and competitive advantage.

Founded by experienced analytics and technology leaders, AnalytixHub.ai combines enterprise-grade delivery standards with the agility of a modern data and AI lab. Our teams bring together expertise across data engineering, analytics, business intelligence, and automation to deliver scalable, practical, and outcome-driven solutions.

This is a full-time, on-site Lead Data Engineer role based in Chennai.

The Lead Data Engineer will be responsible for designing, developing, and maintaining scalable data platforms and modern data pipelines to support analytics, reporting, and AI initiatives. The role involves building robust ETL/ELT frameworks, architecting data models and warehouses, ensuring data quality and governance, and optimizing platform performance and cost.

The candidate will work directly with clients and business stakeholders to understand requirements, define technical solutions, and lead successful delivery execution. This role also requires mentoring engineers, driving engineering best practices, and leading technical teams across multiple initiatives.

• Strong hands-on experience in SQL and Python with the ability to build scalable and high-performance data solutions.
• Strong expertise in at least one cloud platform – AWS, Azure, or GCP and associated data services (Data Lake, ETL, orchestration, compute, storage, monitoring).
• Proven experience designing and implementing scalable data architectures, data pipelines, and modern data platforms.
• Strong understanding of data modeling, data warehousing, ETL/ELT frameworks, and data integration patterns.
• Experience working with large-scale structured and semi-structured datasets.
• Strong knowledge of orchestration and transformation tools and modern data engineering practices.
• Excellent communication and stakeholder management skills, with demonstrated experience in client-facing roles and leading technical discussions.
• Proven ability to gather business requirements and translate them into scalable technical solutions.
• Prior experience leading engineering teams, mentoring developers, driving delivery ownership, and managing project execution.
• Experience with code versioning, CI/CD practices, and deployment automation.
• Ability to work in a fast-paced environment and contribute to technical strategy and roadmap planning.
• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent practical experience).
• Experience with Databricks, Spark/PySpark, Airflow, Snowflake, or modern data platform