Data Automation Engineer

We are seeking a delivery-focused Data Automation Engineer to design and implement innovative automation solutions across a Microsoft Azure-based data analytics platform. This role partners closely with engineering teams and stakeholders to translate business requirements into scalable data engineering and AI-enabled solutions.

The ideal candidate is hands-on with Azure Data Factory, Synapse Pipelines, Apache Spark, Python, and SQL, and brings experience building reliable ETL pipelines across SQL and NoSQL environments. This role emphasizes performance optimization, automation, and proactive data quality within Agile DevOps delivery models., Data Engineering & Automation

• Develop high-performance data pipelines using Azure Data Factory, Synapse Pipelines, Spark Notebooks, Python, and SQL.
• Design ETL workflows supporting advanced analytics, reporting, and AI/ML use cases.
• Implement data migration, integrity, quality, metadata, and security controls across pipelines.
• Monitor, troubleshoot, and optimize pipelines for availability, scalability, and performance.

Performance Testing & Optimization

• Execute ETL performance testing and validate load performance against benchmarks.
• Analyze pipeline runtime, throughput, latency, and resource utilization.
• Support tuning activities (e.g., query optimization, partitioning, indexing).
• Validate data completeness and consistency after high-volume processing.

Platform Collaboration & DevOps Support

• Collaborate with DevOps and infrastructure teams to optimize compute, memory, and scaling.
• Maintain versioning and configuration control across environments.
• Support production, testing, development, and integration environments.
• Actively participate in Agile delivery processes including Program Increment planning.

• Bachelor's degree in Computer Science or related field.
• 2+ years of experience with SQL, T-SQL, DAX/MDX, Python, or PySpark.
• Experience designing and building ETL solutions within cloud environments.
• Hands-on experience with Azure Data Factory, Synapse, or Azure Data Lake.
• Experience with Microsoft BI tools including SQL Server, SSIS, SSRS, SSAS, or Power BI.
• Familiarity with Azure/AWS CLI automation using Bash or PowerShell.
• Experience with Git or Azure DevOps for release/version management.
• Experience working in Agile environments.
• Ability to obtain a Public Trust clearance required.

-Preferred Qualifications

• Certification in Azure, Power BI, AI, or AWS data engineering.
• Experience with Generative AI tools or data automation use cases.
• Familiarity with REST APIs, Docker, or enterprise ETL tools.
• Exposure to performance tuning, query analytics, or data profiling.
• Knowledge of ARM/Bicep templates or RBAC access controls.
• Familiarity with data lineage or governance tools (e.g., Microsoft Purview).

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