Senior Data & Analytics Enablement Analyst - Data Integration Specialist

Senior Analysts, Data & Analytics Enablement, Data Integrations

Job Description Summary

We are seeking an experienced Senior Analysts, Data & Analytics Enablement to drive the integration and migration of data products across a layered/medallion architecture as part of a large-scale acquisition and platform change programs. This role ensures that data is ingested, curated, quality-checked, and provisioned into the data platform in a manner that preserves business logic, data quality standards, and downstream consumer continuity.

The individual will own the end-to-end data enablement lifecycle during integration — translating transformation logic between platforms, aligning layer definitions and naming conventions, implementing data quality controls, and ensuring that curated data products are available to analytics, reporting, and operational consumers on schedule and in compliance with governance and regulatory standards. This role bridges data engineering, data stewardship, and business stakeholder engagement across both entities.

Job Description

Location: Hyderabad #Hybrid

Key Responsibilities

• Architecture Alignment & Layer Mapping: Assess and document data architecture layers (e.g., raw/staging, intermediate/curated, consumption/marts) and map them to the target organization’s / target platform’s medallion or layered architecture. Identify semantic differences and define a unified layer strategy for the integrated platform.

• Transformation Logic Migration: Inventory all transformation models, business rules, and data curation logic (across tools such as dbt, Python, ETL/ELT platforms). Translate and re-implement this logic within the target platform's tooling and standards, ensuring full preservation of business intent and data lineage.

• Data Quality & compliance controls: Implement standard data quality checks (completeness, uniqueness, referential integrity, timeliness, validity) at each architecture layer for migrated data. Ensure appropriate compliance controls, including PII/PHI masking, row-level security, and classification-based access policies — are applied consistently across migrated datasets.

• Data Product Provisioning: Curate and provision cleaned, validated, integration-ready datasets for downstream consumers (analytics teams, BI/reporting, data science, operational systems). Manage provisioning layer schemas and ensure consumer-facing data products meet agreed SLAs for freshness, completeness, and accuracy.

• Cross-Entity Stakeholder Engagement: Partner with domain owners, business analysts, and data consumers from both entities to validate that migrated data products meet business requirements. Facilitate domain-by-domain walkthroughs to confirm business logic preservation, flag gaps, and prioritize remediation.

• Governance, Metadata & Documentation: Register all migrated data assets (schemas, tables, columns, business rules) in the enterprise data catalog. Maintain data dictionaries, business glossary entries, and end-to-end lineage documentation. Ensure compliance with data governance policies, regulatory requirements, and FAIR data principles (Findable, Accessible, Interoperable, Reusable).

• Continuous Improvement: Identify opportunities to optimize pipeline performance, reduce data latency, and improve quality automation during and after migration. Evaluate and recommend AI/ML-driven approaches for quality monitoring, anomaly detection, and automated data profiling.

Essential Requirement:

• 3–6 years in data engineering / stewardship / analytics enablement; at least 2 years in migration/integration

• Strong layered data architecture + data warehouse fundamentals (dimensional modeling, slowly changing dimensions, star/snowflake)

• Hands-on with extract-transform-load / extract-load-transform tooling + cloud data platforms

• Strong Structured Query Language and Python. Data modeling + data quality frameworks

• Governance: metadata, cataloging, lineage, classification.

• Proven large-scale migration/integration experience (logic + curated datasets).

• Layer mapping/reconciliation across two architectures.

• Translating transformation logic between tools/frameworks.

Desirable Requirements:

• Experience with orchestration tool migration (e.g., transitioning from one scheduler/orchestrator to another — such as Dagster to Airflow, Control-M to Airflow, or similar).

• Familiarity with data catalog and lineage tools (e.g., Collibra, Alation, Atlan, Purview) and experience registering assets during a migration.

Commitment to Diversity & Inclusion

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

 

Accessibility and accommodation

Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to perform the essential functions of a position, please send an e-mail to diversityandincl.india@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

 

Skills Desired

Advertising Campaigns, Alteryx, Analytical Thinking, Brand Awareness, Business Networking, Curiosity, Digital Marketing, Marketing Communications, Marketing Plans, Marketing Strategy, Media Campaigns, Process Documentation, Statistical Analysis, Strategic Marketing

Experience Level

Senior Level