Data Engineering Lead

Ubifly Technologies; Chennai District; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

The ePlane Company in India seeks a Data Engineering Lead to architect and own data infrastructure across digital systems, market intelligence, and product operations. Lead ETL/ELT pipelines, ensure data integrity, and provide a robust data backbone for cross-functional teams to leverage insights for decision-making.

You will design the data warehouse, implement lineage tracking, and establish secure data access with scalable architectures, while promoting high standards for code quality and

Qualifications

• 8+ years in Data Engineering with experience leading engineering teams.
• Expertise in building scalable data pipelines and data governance.
• Strong knowledge of data warehouse design and data modeling.
• Experience with data quality frameworks and security protocols.
• Able to design auditable data lineage and metadata management.

Responsibilities

• Build scalable ETL/ELT pipelines to handle high-velocity streaming data and batch processing.
• Implement data integrity checks, metadata management, and security protocols.
• Provide the data backbone for the MDO, Commercialisation, and engineering teams to ensure seamless data flow.
• Maintain the highest standards for code quality, including conducting rigorous code reviews, developing comprehensive unit tests, and producing clear, thorough documentation.
• Design and implement the data warehouse: raw data lake + structured analytical warehouse with clear separation of raw, cleaned, and modelled data layers.
• Implement data lineage tracking: every number that enters a model output must be traceable back through transformations to its original source record.
• Design the data access layer for the appropriate teams and create experimental, isolated, and research sandboxes

Skills

Team Leadership

Data Governance

ETL/ELT

Data Lineage

Code Quality

Tools

Apache Spark

Kafka

Airflow

Cloud Platforms (AWS/Azure/GCP)

NoSQL Databases

Relational Databases

Vector Databases

Docker

Kubernetes

Job description

The ePlane Company is at the forefront of India's urban air mobility revolution. Incubated at IIT Madras, we are a deep-tech startup dedicated to designing and building the world's most compact electric flying taxi. Our mission is to make door-to-door flying a reality, drastically reducing commute times and decongesting our cities for a cleaner, greener future. We're a passionate team of engineers, designers, and visionaries working on cutting-edge technology, and we're looking for brilliant minds to help us take flight.

Chart the Course for the Future of Flight

This role builds and owns the data infrastructure across digital systems, market intelligence, and product operations. The data engineering lead is also the programme's data governance officer: the person who ensures that when anyone asks where does that number come from, the answer is a documented, auditable data lineage

Roles and Responsibilities

Build scalable ETL/ELT pipelines to handle high-velocity streaming data and batch processing.

Implement data integrity checks, metadata management, and security protocols.

Provide the data backbone for the MDO, Commercialisation, and engineering teams to ensure seamless data flow.

Maintain the highest standards for code quality, including conducting rigorous code reviews, developing comprehensive unit tests, and producing clear, thorough documentation

Design and implement the data warehouse: raw data lake + structured analytical warehouse with clear separation of raw, cleaned, and modelled data layers

Implement data lineage tracking: every number that enters a model output must be traceable back through transformations to its original source record,

Design the data access layer for the appropriate teams and create experimental, isolated, and research sandboxes

Requirements

Required Qualifications

8+ years in Data Engineering with experience leading engineering teams.

Expertise in Apache Spark/Kafka, Airflow, and cloud infrastructure (AWS/Azure/GCP).

Advanced knowledge of NoSQL, Relational, and Vector databases.

Proven understanding of fundamental data structures and the ability to apply them to solve complex problems.

Cloud data warehouse experience: Schema design, query optimisation, cost management

Comfort with large, messy, multi-source datasets

Experience with data quality frameworks

Experience with Containerization (Docker/Kubernetes)

Preferred Qualifications

Experience at a data-intensive platform company where data pipelines directly powered business-critical decisions

Exposure to time-series data pipelines: has built systems that ingest, store, and serve temporal data cleanly (traffic growth time-series, economic indicators)

Understanding of mathematics, particularly linear algebra and probability theory