Job Description

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.