We are seeking a Senior Data Engineer with strong expertise in ETL, Microsoft Azure, SQL, Power BI, and Power Platform automation to support our growing Data Science and Data Analytics initiatives. You will play a crucial role in developing end-to-end data pipelines, designing scalable data architectures, and enabling business process automation through Microsoft's low-code tools.
This is a cross-functional role that requires close collaboration with data scientists, operations, platform, and business teams to deliver reliable data, actionable insights, and streamlined operations across the enterprise.
Key Responsibilities:
Data Engineering & Infrastructure:
Design, build, and maintain robust data pipelines and ETL/ELT workflows using Azure Data Factory, Azure Synapse, and Azure Data Lake.
Develop and optimize SQL queries and data transformations for efficient data processing.
Implement and evolve python script to support reporting, analysis, and AI use cases.
Power BI & Analytics Enablement:
Design, build, and maintain high-performance, scalable Power BI dashboards and datasets.
Build optimized Power BI semantic models, define DAX measures, and publish reusable dataflows.
Enable self-service analytics through shared datasets and clearly documented business logic.
Power Platform Automation:
Design and implement automated workflows using Power Automate to streamline repetitive business tasks and data refresh processes.
Build lightweight internal applications using Power Apps integrated with data from SharePoint, Power BI and SQL sources.
Integrate Power Platform tools with Azure and Office 365 for seamless business process automation.
Azure Cloud Platform:
Deploy and manage cloud-based data solutions using Azure services including:
o Azure SQL Database / Synapse Analytics
o Azure Data Factory
o Blob Storage, File Share and Key Vault
AI Support:
Provide clean, curated, and version-controlled datasets for data science experimentation and ML model training.
Assist in feature engineering, model scoring, and deployment of analytics-ready datasets to cloud environments.
Governance, Documentation & Best Practices:
Ensure compliance with data privacy, security, and governance policies.
Implement data validation, quality checks, and monitoring in all pipelines.
Maintain comprehensive documentation of data assets, workflows, and technical procedures.
Required Qualifications:
Required Qualifications:
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
6+ years of experience in data engineering, with a strong track record supporting AI and business analytics teams.
Advanced proficiency in SQL, including complex query writing and performance tuning.
Proficiency in Python for data processing.
Expertise in the Microsoft Azure ecosystem, including:
o Azure Data Factory
o Azure SQL / Synapse Analytics
o Azure Data Lake Gen2
o Azure Functions (nice to have)
Deep experience with Power BI, including data modeling, DAX, dataflows, and dashboard development.
Practical experience in designing and automating business workflows using Power Automate and building apps in Power Apps.
Experience with version control systems (Git), CI/CD tools, and data pipeline monitoring solutions.
Strong interpersonal and communication skills; ability to explain complex technical issues to non-technical stakeholders.
Preferred Skills:
Experience with Azure DevOps, PowerShell, or scripting for task automation.
Knowledge of data governance tools like Azure Purview.
Experience with Agile methodologies and working in cross-functional teams.