Data Engineering Lead
First seen by Alion on Sep 2, 2026.
Work Mode : WFO 5 Days office or 3 Days in a Week
Job Location : Hyderabad
Job Type : Full Time
Your Role :
As the Data Engineering Lead, you will be a leader of the data engineering team working on in-house products in for Data Foundation Collaborating closely with Product Owner(s), Product Architect(s) and other DataOps teams you will need to understand the business needs, helping Product Architect(s) to convert those needs into solution architecture specifications and services in line with overall engineering standards and roadmaps.
You will be driving excellence in engineering practices to deliver high-quality solutions throughout the software development lifecycle in our IT landscape.
This role involves hands-on development work. This role will directly report to Engineering Manager.
Required skills & Experience :
- Min 10 years of IT experience is required including min 7 - 8 yrs of Data Engineering experience.
- Min 3 - 4 years of experience in Team Management and Stakeholder Management.
- Strong experience in Azure cloud data services & technologies.
- Azure Databricks, Unity Catalog, Delta live table (Experts).
- Expert in Python, Pyspark and SQL (Expert in Python).
- Data Modelling & Architecture (Experts).
- ETL pipeline design (Experts).
- Azure Data Factory.
- Azure DevOps.
- Logging and Monitoring using Azure / Databricks services.
- Apache Kafka.
Responsibilities :
- Lead a team of experienced team members of Data Engineers in designing, developing, and delivering scalable, reliable, and high performing software solution.
- Lead the design, development, and maintenance of scalable data pipelines and ETL processes.
- Monitor and optimize data infrastructure performance, identifying and resolving bottlenecks and issues.
- Lead the team from a technical standpoint, and drive operational excellence, including code reviews, design reviews, testing, and deployment processes.
- Be an individual contributor (~60%) engineering the software products/solutions, jointly with the team and ensure that the team adheres to coding standards, best practices, and architectural guidelines, oversee team spirit and team performance, guide and mentor team members.
- Oversee the implementation of the technical architecture, solve immediate technical challenges.
- Implement good practices, coding standards and modern architecture for DataOps; be a go-to-person for technical decisions and problem-solving within the team and Ensure that the execution of DataOps is in place in the team's daily work, Inspire, advise, and drive the selection of development approach, coordinate software development and address technical debt in the team.
- Hire, onboard, mentor, and develop top engineering talents, fostering a culture of learning, collaboration, and continuous improvement.
- Lead technical discussions with other teams/departments and oversees state-of-art quality of the stack.
- May be involved in cross-functional discussions, representing the domain in broader technical discussions across domains.
- Responsible for designing and improving processes that enhance efficiency and quality communication with Engineering Manager, Product Owner, Business Analyst and Scrum Master to align on project sprint goals, timeline and resource allocation.
Skills
Data Engineering, Engineering Management, Azure, Data Infrastructure, Azure Databricks, Python, PySpark, Data Modeling, ETL, Data Pipeline