Sr. Analyst Engineer at Zinnov… · Hybrid -…

Zinnov is hiring for the role of Professional, Sr. Databricks Platform Engineer on behalf of our Global MNC MedTech client company - a company where technology sits at the centre of everything: powering how the core business operates day to day and shaping the products and digital solutions that will define the future of patient care. This role is part of the company's establishment of its new India Global Capability Centre (GCC) in Bengaluru, which will drive enterprise technology, digital transformation and innovation for global operations.

The role works closely with data architecture, engineering, analytics, security, governance, and cloud infrastructure teams to operate the Databricks Lakehouse as a secure, scalable, observable, and cost-efficient enterprise platform.

Role & responsibilities

• Design and maintain the enterprise semantic/metrics layer including certified measures, dimensions, hierarchies, relationships, and reusable business logic.
• Develop modular, version-controlled transformation and semantic models using dbt, dbt Semantic Layer/MetricFlow, or equivalent analytics-engineering frameworks.
• Integrate governed semantic models with BI platforms such as Power BI, Tableau, SAP Analytics Cloud, or equivalent to maintain consistent metrics across consumption tools.
• Curate the internal data marketplace by onboarding, cataloging, documenting, certifying, and publishing data products for discoverability and self-service access.
• Manage metadata including business descriptions, ownership, lineage, freshness, quality indicators, usage guidance, and access workflows using platforms such as Unity Catalog, Collibra, Purview, Alation, Atlan, DataHub, or equivalent.
• Engineer web-based and embedded analytics experiences using JavaScript/TypeScript, React, HTML/CSS, REST/GraphQL APIs, and BI embedding SDKs where required.
• Optimize semantic performance through aggregations, caching, query pushdown, incremental materialization, indexing/clustering, and model tuning.
• Implement row-level, object-level, and attribute-based access controls across semantic models, catalogs, and analytics experiences.
• Instrument usage telemetry and adoption analytics to identify unused assets, rationalize duplicate reporting, and prioritize the data-product roadmap.
• Support migration of legacy reporting logic into the governed semantic layer and create documentation, training, and standards that increase analytical literacy.

Preferred candidate profile

• 6+ years of progressive experience in analytics engineering, business intelligence, semantic modeling, or data modeling within an enterprise environment.
• Hands-on experience designing and governing a semantic layer or metrics layer used by multiple downstream analytics tools.
• Advanced SQL skills and strong knowledge of dimensional modeling, star/snowflake schemas, metric definitions, data marts, and performance optimization.
• Experience with dbt or an equivalent modular transformation framework including testing, documentation, Git/version control, and deployment workflows.
• Strong experience with one or more BI platforms such as Power BI, Tableau, or SAP Analytics Cloud and their semantic modeling/security capabilities.
• Working knowledge of data catalogs, lineage, metadata, data products, and marketplace concepts using tools such as Unity Catalog, Collibra, Purview, Alation, Atlan, or equivalent.
• Experience partnering with business and governance stakeholders to define, certify, and document shared enterprise metrics.
• Working knowledge of APIs and web/embedded analytics integration patterns.

Preferred

• Hands-on experience with dbt Semantic Layer/MetricFlow, Power BI semantic models/Fabric, Looker/LookML, or comparable governed metrics technologies.
• Experience with JavaScript/TypeScript, React, HTML/CSS, REST or GraphQL APIs, and embedded BI SDKs.
• Cloud data platform experience with Databricks, Snowflake, Azure, AWS, or modern Lakehouse architectures.
• Experience with data mesh/data-as-a-product operating models and marketplace adoption/usage analytics.
• Experience applying GenAI/LLM capabilities to metric documentation, natural-language data access, metadata enrichment, or analytics experiences.
• MedTech, Life Sciences, healthcare, or other regulated-industry experience; relevant dbt, Power BI, Tableau, Snowflake, or cloud certification.

Additional Information

• Language: English proficiency required; additional regional languages are a plus.
• Travel: Limited domestic or international travel may be required, typically less than 10%.