Job Description
Greetings from Indus Ind Bank!!
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We are currently hiring for Lead Data Engineer
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Location- Mumbai
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Experience- 10 to 17 Yrs
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Role Details:
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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.
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Overall, Job Description
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Data Modeling & Architecture
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- Expertise in:
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- Conceptual, Logical & Physical Data Modeling
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- Dimensional modeling (Star/Snowflake schemas)
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- Experience building models optimized for:
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- Lakehouse (Databricks)
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- Analytical workloads
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- Strong understanding of:
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- Data partitioning, indexing, data skipping, caching techniques
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Programming & Transformation
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- Strong hands-on skills in:
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- PySpark (mandatory)
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- Python for data transformation and automation
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- Experience implementing:
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- Data pipelines using Databricks workflows / jobs
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- Reusable transformation frameworks
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Integration & Advanced Capabilities
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- Experience with:
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- API integration and data ingestion frameworks
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- CI/CD in Azure (Azure Dev Ops, Git integration with Databricks)
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- Infrastructure as Code (ARM templates / Terraform – good to have)
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Analytics & BI
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- Experience integrating data platforms with:
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- Power BI (preferred)
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- Ability to:
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- Create semantic layers and datasets for business consumption
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- Enable self-service analytics
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Good to Have
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- Knowledge of:
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- Azure Purview / Microsoft Fabric (emerging tools)
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- Data governance frameworks
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- Streaming analytics and real-time pipelines
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Key Responsibilities
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- Hands-On Technical Leadership
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- Lead by example with active hands-on development in Azure Databricks
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- Design and implement:
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- Scalable lakehouse architectures
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- High-performance data pipelines
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- Review and guide code, architecture, and best practices across the team
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Team Leadership
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- Manage and mentor a team of:
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- Data Engineers
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- Data Analysts
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- Drive best practices in:
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- Code quality
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- Data engineering standards
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- Agile delivery
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Architecture & Solution Design
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- Translate business needs into:
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- End-to-end Azure data architecture
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- Scalable and reusable data models
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- Define standards for:
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- Data ingestion, transformation, storage, and serving layers
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Stakeholder Engagement
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- Collaborate with business stakeholders to:
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- Understand requirements
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- Translate into technical solutions
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- Deliver actionable insights
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- Act as the primary data advisor for the business vertical
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Data Governance & Quality
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- Implement and enforce:
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- Data governance policies
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- Data quality frameworks
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- Metadata management (cataloging, lineage)
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Optimization & Innovation
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- Continuously optimize:
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- Databricks jobs (performance & cost)
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- Data storage and query performance
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- Stay current with:
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- Azure and Databricks advancements
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- Modern data engineering practices (Medallion architecture, Data Ops)
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Education and Work Experience Requirements:
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EDUCATION
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Essential requirements:
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- Bachelor’s degree in Computer Science or equivalent
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- Preferred certifications:
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- Azure Data Engineer (DP-203)
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- Azure Fundamentals (AZ-900)
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- Databricks certifications (Associate/Professional)
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Preferred: Technical Skills
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Core Data Engineering (Must-Have)
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- Deep expertise in Azure Data Platform, including:
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- Azure Databricks (core focus) – Spark (PySpark/Scala), Delta Lake, notebooks, workflow orchestration
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- Azure Data Factory (ADF) – pipeline orchestration, integration runtime, monitoring
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- Azure Data Lake (ADLS Gen2) – storage design, partitioning strategies
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- Azure Synapse Analytics – data warehousing and SQL analytics
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- Strong hands-on experience with:
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- Data lakehouse architecture (Delta Lake preferred)
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- ETL/ELT frameworks and data ingestion patterns
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- Streaming (valuable to have): Structured Streaming, Event Hub, Kafka
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WORK EXPERIENCE
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- 10–17 years of overall experience
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- Minimum 7+ years of hands-on experience in:
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- Data engineering
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- Data modeling in large-scale enterprise data platforms
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- Strong experience in Azure-based data ecosystems and Databricks implementations
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- Proven track record of leading data engineering and analytics teams
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Interested candidates kindly share your updated profile on
[email protected] or apply on our ATS portal link below for better tracking:
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Requition No: 87628
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📌 Data Engineering Lead (Mumbai)
🏢 IndusInd Bank
📍 Mumbai