The Technical Lead will drive the migration of our Microsoft-based data platforms (on-premise and Azure) to Databricks, providing hands-on mentorship and technical oversight for the data engineering team.

Please note: This is a pure technical leadership role, focused on architecture and execution rather than project management or Scrum facilitation.

The focus is on:

Technical direction
Engineering quality
Delivery execution
Removing technical blockers
Ensuring consistency and scalability across teams

The Technical Lead will act as the bridge between architecture, engineering teams, and delivery, while remaining capable of hands-on contribution when needed.

Key Responsibilities

Technical Leadership & Coordination

Act as the technical reference point for data engineers during migration and transformation activities
Break down high-level migration objectives into clear technical tasks and implementation approaches
Ensure alignment to target architecture and standards (Databricks, cloud-native patterns)
Review designs, pipelines, and implementations to ensure quality and consistency
Actively remove technical blockers for the engineering teams

Migration & Transformation Execution

Lead the migration of data pipelines from:
o SQL Server / SSIS (on-prem)

o Azure Synapse

o Azure SQL / SQL Managed Instances→ into Databricks (Lakehouse architecture)

Define and enforce best practices for:
o Data ingestion

o Transformation patterns

o Performance optimization

o Cost awareness

Support coexistence scenarios during the transition phase

Hands-on Engineering (as needed)

Contribute directly to development when required:
Databricks notebooks (PySpark / SQL)
Ingestion pipelines
Refactoring legacy logic




Build reference implementations and examples for the team
Support troubleshooting and performance tuning

Team Enablement

Mentor data engineers and help upskill them towards Databricks and modern data engineering practices
Facilitate technical discussions, refinement sessions, and solution reviews
Ensure development stays on track, even across multiple parallel workstreams
What This Role Is NOT

Not a Project Manager
Not a Scrum Master
Not a pure Architect
Not 100% hands-on developer
It is a delivery-focused technical leadership role.

Required Technical Skills

Core Platform Knowledge

Strong experience in Data Engineering
Proven experience leading engineers in complex data environments
Hands-on experience with:
Databricks (mandatory)
PySpark & Spark SQL
Lakehouse concepts (Bronze / Silver / Gold)
Microsoft & Azure Background (must-have due to migration context)

Solid experience with:
SQL Server
Azure SQL / SQL Managed Instances
Azure Synapse
Ability to translate legacy ETL logic into modern Spark-based pipelines
Cloud & Engineering Practices

Experience with Azure cloud environments
Understanding of:
CI/CD for data pipelines
Git-based development
Infrastructure-as-code concepts (nice to have)
Robust SQL skills
Performance tuning and troubleshooting experience

Qualifications

Bachelor’s or Master’s degree in Computer Science, or a strictly related technical discipline.

7-10 years of specialized experience in Data Engineering.

Preferred background in the Retail sector, with an understanding of industry-specific data challenges.

Technical Leadership

Lead the DE Team/Owning the DE tasks (Design, build, maintain entire pipelines)

Data quality/Integrity/availability across the system

📌 Data Engineering Technical Lead (Hyderabad)
🏢 Texplorers
📍 Hyderabad