Microsoft Power Bi And Data Scientist Engineer

Overview We are seeking an experienced

Data Engineer

with expertise in

Azure Data Factory, Azure Synapse Analytics, and Microsoft Fabric

to join our growing data engineering team. The ideal candidate will design, build, and optimize

data pipelines, data lakes, and data warehouses

on Azure to empower data scientists, analysts, and business stakeholders. This role involves leveraging

ADF for ETL processes, Synapse for analytics, and Microsoft Fabric for modern data workflows

to deliver scalable, secure, and efficient data solutions.

Responsibilities

Design, develop, and deploy ETL pipelines using Azure Data Factory (ADF).

Integrate ADF with external sources (SQL, NoSQL, REST APIs, flat files, Azure Blob, Data Lake).

Implement data validation, transformation rules, and error handling within pipelines.

Automate data movement and orchestration across storage, databases, and analytics platforms.

Use Mapping Data Flows for advanced transformations and aggregations.

Build and manage data lakes and warehouses on Azure Synapse Analytics.

Design serverless SQL pools, Spark pools, and data integration pipelines in Synapse Studio.

Optimize Synapse performance for batch processing and real-time analytics.

Develop OLAP and OLTP data models for reporting and exploration.

Implement Microsoft Fabric for end-to-end data integration across Azure services.

Leverage Fabric’s Lakehouses, Warehouses, and Data Pipelines for analytics and AI-driven insights.

Enable collaborative workflows across data engineering, data science, and BI teams.

Build self-service BI solutions within Fabric to empower business users.

Design cloud-native architectures for scalable and cost-effective data systems.

Ensure data governance, security, and compliance (GDPR, CCPA).

Implement RBAC, encryption, and Azure Purview for data cataloging, lineage, and auditing.

Optimize data storage, compute resources, and ensure high availability.

Build and maintain CI / CD pipelines using Azure DevOps, GitHub Actions, or Azure Pipelines.

Automate workflows with Azure Logic Apps and Power Automate.

Monitor and troubleshoot pipeline performance to minimize downtime.

Continuously improve data engineering processes for automation, scalability, and maintainability.

Work closely with cross-functional teams including data scientists, analysts, and business stakeholders.

Provide Power BI integration for advanced dashboards and reporting.

Support AI / ML workflows using Azure Machine Learning when required.

Report to the Project Manager and execute assigned data engineering tasks.

Required Skills & Experience

6+ years of hands-on experience in data engineering and cloud data architecture.

Strong expertise in :

Azure Data Factory (ADF) – ETL and pipelines

Azure Synapse Analytics – data lakes, warehouses, modeling, analytics

Microsoft Fabric – data integration, lakehouses, warehouses, and collaborative workflows

Proficiency in SQL / T-SQL and Azure SQL Database.

Knowledge of Azure Blob, Data Lake, and Azure SQL storage.

Experience with Hadoop, Spark, Databricks within Azure ecosystems.

Familiarity with DevOps practices, CI / CD pipelines, and automation.

Strong background in data governance, quality, and security in cloud environments.

Exposure to Power BI, Azure ML, or other BI / AI tools (preferred).

Preferred Certifications (Not Mandatory)

Microsoft Certified : Azure Data Engineer Associate

Microsoft Certified : Azure Synapse Analytics

Microsoft Certified : Azure AI Engineer Associate

Microsoft Certified : Azure Solutions Architect Expert

Qualifications

Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, Business, or related field.

Location : Onsite / Hybrid (as per project requirement)

Reporting To : Project Manager

Work Schedule : Standard office hours (flexibility as per project needs)

Skills : azure, power bi, transact-sql (t-sql), data lake, adf, ai / ml, cloud architecture, rbac, olap, etl pipelines

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