Job Description

Roles & Responsibilities

Architectural Leadership: Define and evolve the enterprise data architecture aligned with enterprise business goals and digital transformation initiatives.
Platform Expertise: Lead the design and optimization of end-to-end data solutions on Microsoft Azure and Databricks, covering the complete data lifecycle and ensuring seamless data integration, governance, and performance.
Data Strategy & Governance: Establish data standards, policies, best practices, design principles and governance frameworks to ensure data quality, data lineage, data observability, security, and compliance.
Collaboration & Influence: Partner and interact with key business and IT client stakeholders, data and IT teams to translate business requirements into scalable data solutions.
Innovation & Optimization: Drive adoption of modern data architectures including headless architecture, data lake and lake house, real-time analytics, Lambda and Kappa Architectures and AI/ML enablement.
Technical Oversight: Provide guidance and hands on expertise on data modeling, metadata management, data pipeline design and orchestration, and cloud-native architecture design and best practices.
Proven experience as a Data Architect with knowledge on Enterprise Architecture (EA frameworks like TOGAF/Zachmann etc.) in large-scale data environments.
Proven experience working as Solution Architect in the Data and AI/ML tech domain with Public sector experience
Deep expertise in Azure Data and Integration Services (e.g., Azure Data Lake Gen2, Synapse, MS Fabric, Data Factory, Purview, Event Hub).
Hands-on experience with Databricks for big data processing, analytics, and machine learning leveraging Data Lake house architecture, delta lake
Strong understanding of data modeling (Dimensional Data modelling expertise), ETL/ELT pipelines, and data governance.
Familiarity with modern data architecture paradigms (e.g., data lake,lakehouse, data mesh, data fabric, Unity Catalog, Medallion Architecture, lambda architecture etc.)
Experience in designing AI/ML platforms and Business Intelligence and insights (leveraging tools like Power BI)
Familiarity with traditional Data warehousing architecture and tools like Informatica etc. and multi dimensional data modeling
Experience in designing Master Data Management systems (using MDM tools and patterns), implementing Data Quality
Experience designing data systems using APIs and microservices design patterns, Kafka
Experience working with Spark, Python, Hadoop, Apache Iceberg, Apache Hudi etc.
Excellent communication and stakeholder management skills.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.

Desired Candidate Profile

Proven expertise in SQL and NoSQL databases, with hands-on experience in database management systems.
Relevant certifications such as Certified Data Management Professional (CDMP) or AWS Certified Data Analytics.
Experience working in industries such as finance, healthcare, or technology to understand specific data challenges.

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