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Aerospace • Artificial Intelligence • Cloud • Machine Learning • Software • Cybersecurity • Defense
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Designs and customizes software applications, manages releases, gathers stakeholder requirements, mentors junior engineers, maintains technical documentation, evaluates performance metrics, and partners with Quality Assurance to ensure reliable, compliant software. The role also uses market trends to guide product improvements and participates in peer programming, design sprints, and prototyping. Requires independent judgment, consistent attendance, and flexibility to work nights, weekends, and variable schedules.
Lead enterprise data architecture and modernization initiatives using Microsoft Fabric, Azure, Databricks, and Apache Spark. Design cloud-native lakehouse platforms, ingestion and transformation frameworks, governance models, security controls, and scalable batch and real-time pipelines. Establish architecture standards, medallion patterns, lineage, metadata, data quality, and performance optimization. Collaborate with business and engineering stakeholders, lead architecture reviews, translate requirements into technical solutions, and mentor data engineering teams.
Job Summary
- We are seeking an experienced and highly skilled Data Architect with strong expertise in Microsoft Fabric, Azure Data Platform, Databricks, and Apache Spark to lead the design and implementation of enterprise-scale data modernization initiatives.
- The ideal candidate will have extensive experience architecting cloud-native data platforms, defining data strategies, and delivering scalable, secure, and high-performing data solutions across complex business environments.
- This role requires deep technical knowledge of Microsoft Azure data services, modern data architecture patterns, data governance frameworks, and large-scale analytics platforms. Experience within the Insurance domain is highly desirable.
Key Responsibilities
Data Architecture & Strategy
- Define and drive enterprise data architecture strategies aligned with business objectives and technology roadmaps.
- Design scalable, secure, and high-performance data platforms leveraging Microsoft Fabric, Azure, and Databricks ecosystems.
- Establish architecture standards, best practices, reusable design patterns, and governance frameworks for enterprise data solutions.
- Lead cloud data modernization and migration initiatives from legacy platforms to cloud-native architectures.
- Create architecture blueprints, reference architectures, and implementation roadmaps.
Microsoft Fabric Leadership
- Architect and implement end-to-end solutions using:
- Microsoft Fabric Lakehouse
- Fabric Data Warehouse
- Data Pipelines
- Real-Time Analytics
- OneLake
- Power BI Integration
- Design Medallion Architecture (Bronze, Silver, Gold layers) within Microsoft Fabric.
- Drive Fabric deployment strategies, performance optimization, and environment governance.
- Implement Fabric security, access controls, lineage, monitoring, and data lifecycle management.
Azure Data Platform Architecture
- Design and implement enterprise data solutions using:
- Azure Data Factory (ADF)
- Azure Data Lake Storage Gen2 (ADLS)
- Azure Synapse Analytics
- Azure Key Vault
- Azure Event Hub
- Azure Functions
- Azure DevOps
- Define ingestion, transformation, storage, and consumption frameworks.
- Drive cloud adoption and optimization initiatives.
Databricks & Big Data Engineering
- Architect and optimize Databricks Lakehouse solutions.
- Lead implementation of:
- Apache Spark
- PySpark
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Auto Loader
- Delta Live Tables
- Design large-scale data pipelines supporting batch and real-time workloads.
- Optimize Spark processing, cluster utilization, and workload performance.
Data Governance & Security
- Define enterprise data governance standards.
- Implement metadata management, lineage, cataloging, and data quality frameworks.
- Partner with security teams to ensure data privacy, compliance, and regulatory adherence.
- Enable business-friendly data discovery and self-service analytics.
Stakeholder Engagement
- Collaborate with business leaders, product owners, engineering teams, and program stakeholders.
- Translate business requirements into scalable technical architectures.
- Lead architecture reviews, design workshops, and solution governance forums.
- Provide technical leadership and mentorship to data engineering teams
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or related field.
- Minimum 10 years of experience in Data Engineering, Data Architecture, or Data Platform leadership roles.
- Strong experience designing and architecting data solutions in cloud environments.
Must-Have Technical Skills
Microsoft Fabric
- Fabric Lakehouse
- Data Warehouse
- OneLake
- Data Pipelines
- Fabric Security & Governance
- Real-Time Analytics
- Power BI Integration
Microsoft Azure
- Azure Data Factory (ADF)
- Azure Data Lake Storage (ADLS Gen2)
- Azure Synapse Analytics
- Azure Key Vault
- Azure Functions
- Azure Event Hub
- Azure DevOps
Databricks
- Azure Databricks
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Delta Live Tables
- Auto Loader
Data Engineering
- Apache Spark
- PySpark
- SQL
- Python
- Data Modeling
- ETL/ELT Design
Architecture & Governance
- Medallion Architecture
- Lakehouse Architecture
- Data Mesh (Preferred)
- Data Governance
- Metadata Management
- Data Lineage
- Data Quality Frameworks
- CI/CD & DevOps Practices
EXL Pune, Mahārāshtra, IND Office
Pune, India
What you need to know about the Pune Tech Scene
Once a far-out concept, AI is now a tangible force reshaping industries and economies worldwide. While its adoption will automate some roles, AI has created more jobs than it has displaced, with an expected 97 million new roles to be created in the coming years. This is especially true in cities like Pune, which is emerging as a hub for companies eager to leverage this technology to develop solutions that simplify and improve lives in sectors such as education, healthcare, finance, e-commerce and more.
