Lead Data Engineer

Problem solvers who don’t just move data but build scalable, reliable data platforms that drive intelligent business decisions.

As a Lead Data Engineer, you will design, build, and scale data platforms that power AI-driven products and analytics solutions. You will work closely with data scientists, product managers, and engineering teams to enable seamless data flow, storage, and processing for enterprise use cases.

Data Platform Development – Design and build scalable data pipelines and data lake architectures for high-performance analytics.

End-to-End Engineering – Develop robust data ingestion, transformation, and processing systems from raw data to production-ready datasets.

Cloud-Native Development – Architect and deploy data solutions on AWS, Azure, or GCP with strong DevOps and automation practices.

Big Data Expertise – Work with distributed data processing frameworks like Spark, Hadoop, and Hive to handle large-scale data workloads.

Collaboration – Partner with cross-functional teams to deliver reliable and impactful data solutions.

Best Practices – Ensure data quality, governance, security, and performance through standardization and continuous improvement.

Strong experience in data engineering with proficiency in Python, Scala, or Java.

Hands-on expertise in building scalable data pipelines and distributed systems.

Good understanding of data lake architecture, data warehousing, and relational databases (Oracle, SQL, DB2, Teradata).

Experience with Big Data technologies such as Hadoop, Spark, Hive, and HBase.

Familiarity with workflow orchestration tools like Airflow.

Experience with cloud platforms (AWS, Azure, or GCP).

Strong problem-solving mindset with the ability to take ownership and lead initiatives.

Passionate about data, innovation, and solving real-world enterprise challenges.

Chennai-based with flexibility to collaborate with global teams and stakeholders.

Lead and deliver data engineering and analytics projects that create business impact.

Build and optimize data pipelines and infrastructure for scalability and efficiency.

Collaborate with teams to understand requirements and translate them into technical solutions.

Communicate complex data concepts to both technical and business stakeholders.

Drive data strategy and support analytics-driven decision-making.

Design and develop data-driven features and components for product platforms.

Travel to client locations when required.