Senior Data Scientist

Experience: 8 to Not Available years

Location: Others, India

Skills: Microsoft Fabric, Delta Lake, SQL Warehouse, Lakehouse, Data Pipelines, Semantic Models, EPIC Chronicles, Clarity, Caboodle, HIPAA, Python, PySpark, Dataflows Gen2, Azure DevOps, GitHub Actions, Power BI, Machine Learning, Statistical Modeling, Data Mining, SQL

Job Summary
Role Overview - Job Description — Data Engineer /Development Owner - Enterprise Analytics We are seeking a hands-on, technical development owner to lead the design and delivery of enterprise data solutions on Microsoft Fabric. This role requires deep expertise in Delta Lake, SQL Warehouse, Purview, CI/CD, and dimensional modeling, along with robust understanding of EPIC Chronicles, Clarity, Caboodle, and HIPAA-compliant healthcare data engineering. The Data Engineer with the Product Owner to define what to build and owns how it is built, driving technical execution, engineering best practices, and Agile delivery.

Key Responsibilities
Architectural Leadership (Hands-On) • Design and implement star schema, dimensional models, and enterprise data warehouse structures.
• Architect and build Delta Lakehouse, Fabric SQL Warehouse, and Lakehouse solutions.
• Translate complex business requirements into scalable, secure data models and pipelines.

Microsoft Fabric Engineering • Lead development across Delta Lake, SQL Warehouse, Lakehouse, Data Pipelines, and Semantic Models.
• Establish platform-wide engineering standards, automation patterns, and reusable frameworks.

EPIC Data Integration • Lead ingestion, modeling, and harmonization of EPIC data from Chronicles, Clarity, and Caboodle.
• Utilize Fabric Mirroring and Shortcuts to integrate EPIC sources into the Lakehouse and unify them with enterprise datasets.





HIPAA / PHI / PII Compliance • Architect secure, compliant data pipelines for HIPAA-regulated healthcare data.
• Implement governance for PHI/PII masking, RBAC/ABAC access, lineage, auditability, and privacy controls.

Purview Governance & Metadata • Configure and operationalize Microsoft Purview for cataloging, lineage, classification, and sensitivity labeling.
• Enforce metadata, governance, and data quality standards across all data products.

Data Engineering & Quality • Build enterprise-grade pipelines using Python, PySpark, Data Pipelines, Dataflows Gen2.
• Implement reusable ingestion patterns, transformation logic, schema evolution, and data quality checks.

DevOps & CI/CD • Develop and maintain automated CI/CD pipelines (Azure DevOps or GitHub Actions) for Fabric artifacts, SQL objects, and governance configuration.
• Manage Dev → Test → Prod promotion using approvals, gates, and release automation.

Leadership & Agile Execution • Provide technical leadership to engineers, guiding solution design and delivery.
• Partner with the Product Owner on prioritization, planning, and user adoption.
• Stay hands-on - able to dive into code, modeling, pipelines, and platform configuration.

Required Qualifications
• 8+ years of experience in data engineering, data architecture, or enterprise analytics.
• Strong expertise with Microsoft Fabric,



including Delta Lake, SQL Warehouse, and Lakehouse design.
• Proven capability in star schema and dimensional modeling for enterprise data warehousing.
• Experience with EPIC Chronicles, Clarity, and Caboodle data models and healthcare analytics.
• Skilled in integrating EPIC data using mirroring, shortcuts, and ELT patterns.

Key Responsibilities
1. Analyze and interpret large and complex data sets to discover insights and identify trends.
2. Develop and implement custom machine learning models and algorithms to support business objectives.
3. Create interactive and insightful visualizations using power bi to present data driven insights to stakeholders.
4. Collaborate with business stakeholders to understand their goals and translate them into technical requirements.
5. Work closely with data engineers to ensure data quality and accuracy for analysis.
6. Stay updated on industry trends and advancements in data science to continuously improve data methodologies.

Skill Requirements
1. Solid proficiency in data science techniques and tools such as machine learning, statistical modeling, and data mining.
2. Proficiency in power bi for data visualization and reporting.
3. Advanced programming skills in python for data analysis and model development.
4. Solid understanding of database management and sql for data querying and manipulation.
5. Excellent communication and presentation skills to effectively convey complex findings and insights to nontechnical stakeholders.
6. Strong problem-solving and analytical skills to tackle complex data challenges efficiently.

Other Requirements
1. Relevant certifications in data science, Power BI, and Python are a plus.

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