Overview
Overview
We are seeking an experienced Data Architect with over 12 years of expertise in data engineering, big data, and cloud data solutions—particularly on Microsoft Azure. The ideal candidate will have a proven track record of delivering scalable data architectures, building enterprise data lakes, leading complex migrations, and architecting real-time and batch data pipelines. You’ll be responsible for end-to-end architecture—from data ingestion and transformation to governance, analytics, and performance optimization.
Key Responsibilities
We are seeking an experienced Data Architect with over 12 years of expertise in data engineering, big data, and cloud data solutions—particularly on Microsoft Azure. The ideal candidate will have a proven track record of delivering scalable data architectures, building enterprise data lakes, leading complex migrations, and architecting real-time and batch data pipelines. You’ll be responsible for end-to-end architecture—from data ingestion and transformation to governance, analytics, and performance optimization.
Key Responsibilities
- Architecture & Design
- Design scalable, high-performance, cloud-native data architectures using Azure Data Lake, Azure Synapse, and Databricks.
- Develop high-level and low-level architecture documents (HLD/LLD) for modern data platforms.
- Define data models using star and snowflake schemas, optimizing for analytics and query performance.
- Data Engineering & ETL
- Lead the development of ETL/ELT pipelines using Azure Data Factory, PySpark, Spark SQL, and Databricks.
- Manage ingestion of structured and semi-structured data from diverse sources to Azure-based data lakes and warehouses.
- Implement real-time data pipelines using Azure Event Hubs and Structured Streaming.
- Governance & Security
- Define and implement data governance frameworks including lineage, cataloging, access controls, and compliance (e.g., GDPR).
- Collaborate with MDM and governance teams using tools like Informatica AXON and EDC.
- Performance Tuning & Optimization
- Drive cost-efficient architecture design with partitioning, caching, indexing, and cluster optimization.
- Monitor and troubleshoot data pipelines using Azure Monitor, Log Analytics, and Databricks tools.
- Stakeholder Engagement
- Collaborate with data scientists, analysts, business stakeholders, and DevOps teams to deliver robust, scalable data platforms.
- Conduct design reviews and training sessions to support platform adoption and knowledge sharing.
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