Data Engineer

• Data Pipeline Development: Build and maintain efficient, secure, and reliable ELT pipelines using Azure Synapse Analytics and Apache Spark.
• Data Modeling and Warehousing: Develop and optimize data models (e.g., star schemas, snowflake schemas) for data warehousing and analytics, ensuring performance, scalability, and maintainability within Azure Synapse analytics.
• Data Governance and Security: Implement data governance frameworks, including data quality, lineage, and cataloging, using Azure Purview or similar tools. Ensure compliance with security standards and data privacy regulations (e.g., GDPR, CCPA).
• Dev Ops: Take ownership of existing Azure Dev Ops pipelines , source code repositories and branching strategies and produce new artefacts when required . Be responsible for managing all Azure EDW resources using infrastructure as code tooling .
• Performance Tuning : Monitor and optimize the performance of Azure Synapse Analytics, Data Lake , Spark jobs and on-premise SQL Servers including query optimization, partitioning, and indexing strategies.
• Integration and Collaboration : Collaborate with cross-functional teams (e.g., business analysts, report and application developers) to integrate Azure data solutions with other systems, including APIs, third-party tools, and business applications. Provide guidance and mentorship for other less experienced team members.
• Innovation and Strategy : Stay abreast of emerging Azure data technologies, Apache Spark advancements, and industry trends, recommending and implementing innovative solutions to enhance the data platform.

Data Engineer - Senior Manager

Manager, Data Architecture – Automation

Manager, Data Architecture & Automation

Senior Data Engineer, MLOps

Data Engineer – Financial Transactions, Automation

AWS Data Engineer