Data Engineering Lead

The ideal candidate will manage a crossfunctional team of 7-9 engineers (Data Engineers, DevOps Engineers, and FullStack Developers), work closely with onshore Solution Architects, and act as the primary bridge between business stakeholders and technical execution.

Bachelor's/Master's in Engineering 5-8 years

Required Technical Skills

Core Data Engineering Skills

• Strong handson coding experience in Python and SQL
• Solid experience designing and building data pipelines and data platforms
• Proficiency in Teradata SQL with strong query optimization skills
• Handson experience with PySpark for largescale data processing
• Strong understanding of ETL / ELT concepts and data warehousing principles

Cloud & Platform Skills

• Experience with AWS, including services such as:
  • S3
  • EMR
  • Glue
  • Lambda
  • Redshift
• Familiarity with DevOps practices and CI/CD tooling
• Knowledge of Docker and Kubernetes for containerization and orchestration

Functional Skills

• Experience is supporting and delivering datadriven web applications
• Exposure to modern data architecture patterns (lakehouse, microservices, eventdriven systems)
• Experience working in global delivery models with onshore/offshore coordination

Domain & Project Experience

• Experience delivering enterprisescale data platforms or analytics solutions
• Prior exposure to projects involving:
  • Large datasets
  • Performance optimization
  • Multistakeholder delivery environments
• Comfortable managing delivery in fastpaced, clientfacing engagements

Team Size & Stakeholder Interaction Summary

• Team Size: 7-9 engineers (could expand)
• Direct Interaction With:
  • Business stakeholders
  • Onshore Solutions Architect
  • Product owners and client representatives
• Role Nature: Mix of delivery leadership, technical oversight, and people management

Key Responsibilities & DaytoDay Expectations

Delivery & Technical Leadership

• Own endtoend delivery of data engineering and datadriven web solutions
• Design, build, and maintain scalable, reliable data pipelines and data architectures
• Provide handson technical guidance and architectural oversight when required
• Ensure performance, data quality, reliability, and scalability of data systems
• Drive best practices in coding, testing, documentation, deployment, and monitoring

Team Leadership & People Management

• Lead, mentor, and manage a team of 7-9 engineers including:
  • Data Engineers
  • DevOps Engineers
  • FullStack Developers
• Conduct task planning, sprint execution, reviews, and performance feedback
• Ensure efficient collaboration across engineering roles

Stakeholder & Client Collaboration

• Work closely with business stakeholders to translate requirements into technical solutions
• Coordinate with Onshore Solution Architects for solution design, alignment, and delivery
• Act as the primary point of contact for delivery status, risks, and dependencies
• Support engagement planning, delivery commitments, and execution timelines

DevOps & Platform Excellence

• Collaborate with DevOps to implement CI/CD pipelines and automation strategies
• Optimize workflows for cost, performance, and operational efficiency
• Support containerized and cloud-native deployments