Data Engineering Lead

IndusInd Bank; Mumbai; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

IndusInd Bank is hiring a Lead Data Engineer to design and build a cloud-native data platform on Azure, with a focus on Azure Databricks and modern data engineering practices.

The role requires hands-on technical leadership to architect scalable solutions while guiding a team of Data Engineers and Data Analysts to deliver high-quality data products and insights.

Qualifications

• Bachelor’s degree in Computer Science or equivalent.
• Databricks certifications (Associate/Professional) are preferred.
• Strong hands-on experience with Azure Databricks, Delta Lake and Spark (PySpark).
• Experience building lakehouse architectures and data pipelines in Databricks workflows.
• Proven track record of leading data engineering and analytics teams.

Responsibilities

• Lead by example with hands-on development in Azure Databricks.
• Design scalable lakehouse architectures and data models.
• Review code, architecture, and best practices across the team.
• Mentor Data Analysts and Data Engineers.
• Collaborate with stakeholders to translate requirements into data solutions.

Skills

Azure Databricks

PySpark

Python

Data Modeling

Lakehouse Architecture

ETL/ELT

Data Governance

Power BI

Azure Data Services

CI/CD

Education

Bachelor’s degree in Computer Science

Databricks certifications (Associate/Professional)

Tools

Azure DevOps

Terraform

ARM templates

Git

Job description

We are currently hiring for Lead Data Engineer

Experience- 10 to 17 Yrs

Lead, design, and build a cloud-native data platform on Azure, with a strong focus on Azure Databricks and modern data engineering practices. This role requires a hands‑on technical leader who can architect scalable solutions while leading a team of Data Engineers and Data Analysts to deliver high-quality data products and insights.

Overall, Job Description

• Conceptual, Logical & Physical Data Modeling
• Dimensional modeling (Star/Snowflake schemas)
• Experience building models optimized for:
• Lakehouse (Databricks)
• Analytical workloads
• Strong understanding of:
• Data partitioning, indexing, data skipping, caching techniques

Programming & Transformation

• PySpark (mandatory)
• Python for data transformation and automation
• Experience implementing:
• Data pipelines using Databricks workflows / jobs
• Reusable transformation frameworks

Integration & Advanced Capabilities

• Experience with:
• API integration and data ingestion frameworks
• CI/CD in Azure (Azure DevOps, Git integration with Databricks)
• Infrastructure as Code (ARM templates / Terraform – good to have)

Analytics & BI

• Experience integrating data platforms with:
• Power BI (preferred)
• Ability to:
• Create semantic layers and datasets for business consumption
• Enable self-service analytics

Good to Have

• Knowledge of:
• Azure Purview / Microsoft Fabric (emerging tools)
• Data governance frameworks
• Streaming analytics and real‑time pipelines

Key Responsibilities

• Hands‑On Technical Leadership
• Lead by example with active hands‑on development in Azure Databricks
• Design and implement:
• Scalable lakehouse architectures
• Review and guide code, architecture, and best practices across the team
• Manage and mentor a team of:
• Data Analysts
• Drive best practices in:
• Translate business needs into:
• Scalable and reusable data models
• Define standards for:
• Data ingestion, transformation, storage, and serving layers

Stakeholder Engagement

• Collaborate with business stakeholders to:
• Understand requirements
• Translate into technical solutions
• Deliver actionable insights
• Act as the primary data advisor for the business vertical

Data Governance & Quality

• Implement and enforce:
• Data governance policies
• Data quality frameworks
• Continuously optimize:
• Data storage and query performance
• Stay current with:
• Azure and Databricks advancements

Education and Work Experience Requirements:

EDUCATION

• Bachelor’s degree in Computer Science or equivalent
• Preferred certifications:
• Databricks certifications (Associate/Professional)

Preferred: Technical Skills

Core Data Engineering (Must-Have)

• Azure Databricks (core focus) – Spark (PySpark/Scala), Delta Lake, notebooks, workflow orchestration
• Azure Synapse Analytics – data warehousing and SQL analytics
• Strong hands‑on experience with:
• Data lakehouse architecture (Delta Lake preferred)
• ETL/ELT frameworks and data ingestion patterns
• Streaming (good to have): Structured Streaming, Event Hub, Kafka

WORK EXPERIENCE

• 10–17 years of overall experience
• Minimum 7+ years of hands‑on experience in:
• Strong experience in Azure-based data ecosystems and Databricks implementations
• Proven track record of leading data engineering and analytics teams

Requition No: 87628