Data Engineering Lead (Mumbai)

Data Engineering Lead (Mumbai)

14 Aug
|
IndusInd Bank
|
Mumbai

14 Aug

IndusInd Bank

Mumbai

Greetings from IndusInd Bank!!

We are currently hiring for Lead Data Engineer

Location- Mumbai

Experience- 10 to 17 Yrs

Role Details:

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,

Data Modeling & Architecture

- Expertise in:
- 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

- Strong hands-on skills in:
- 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 – valuable 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
- High-performance data pipelines
- Review and guide code, architecture, and best practices across the team

Team Leadership

- Manage and mentor a team of:
- Data Engineers
- Data Analysts
- Drive best practices in:
- Code quality
- Data engineering standards
- Agile delivery

Architecture & Solution Design

- Translate business needs into:
- End-to-end Azure data architecture
- 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
- Metadata management (cataloging, lineage)

Optimization & Innovation

- Continuously optimize:
- Databricks jobs (performance & cost)
- Data storage and query performance
- Stay current with:
- Azure and Databricks advancements
- Modern data engineering practices (Medallion architecture, DataOps)





Education and Work Experience Requirements:

EDUCATION

Essential requirements:

- Bachelor’s degree in Computer Science or equivalent
- Preferred certifications:
- Azure Data Engineer (DP-203)
- Azure Fundamentals (AZ-900)
- Databricks certifications (Associate/Professional)

Preferred: Technical Skills

Core Data Engineering (Must-Have)

- Deep expertise in Azure Data Platform, including:
- Azure Databricks (core focus) – Spark (PySpark/Scala), Delta Lake, notebooks, workflow orchestration
- Azure Data Factory (ADF) – pipeline orchestration, integration runtime, monitoring
- Azure Data Lake (ADLS Gen2) – storage design, partitioning strategies
- 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:
- Data engineering
- Data modeling in large-scale enterprise data platforms
- Strong experience in Azure-based data ecosystems and Databricks implementations
- Proven track record of leading data engineering and analytics teams

Interested candidates kindly share your updated profile on [email protected] or apply on our ATS portal link below for better tracking:

Requition No: 87628

https://app1100.workline.hr/CandidatePortal/18999c40-0af4-47be-88b8-e594e8d8af58/Data-Warehousing-Engineer-Job-in-IBL-House-Office-86846

📌 Data Engineering Lead (Mumbai)
🏢 IndusInd Bank
📍 Mumbai

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