Location: Bangalore – Hybrid / Remote – India

Experience: 10+ Years

Notice Period: Immediate only

If interested apply here or share your resume at [email protected]

About the Role

We are looking for a hands-on Databricks Solutions Architect with strong expertise in enterprise data architecture, data modelling, and Databricks Lakehouse to design and govern a modern enterprise data platform.

The role will own architecture decisions across data ingestion, source-to-target mapping, Bronze–Silver–Gold data models, governance, data serving, and integration boundaries. The ideal candidate is a builder-architect who can work closely with engineering, ML, business, and implementation teams to translate complex data requirements into scalable solutions.

Key Responsibilities

- Own source-to-target architecture and data modelling across operational, finance/vendor, and Workday data domains.
- Design and govern canonical, dimensional, and medallion-based data models across Bronze, Silver, and Gold layers.
- Define the appropriate ingestion strategy for each source using Databricks Lakeflow Connect, SnapLogic/iPaaS, Auto Loader, or other appropriate mechanisms.
- Architect and govern Databricks Lakehouse solutions, including Delta Lake, Unity Catalog, Lakeflow, Lakebase, Lakehouse Federation, and Metric Views.
- Define data standards, conformance rules, business keys, relationships, and data quality principles to support analytics and ML use cases.
- Design data access, governance, security, and API exposure through Unity Catalog and REST/API-based interfaces.
- Architect data interfaces and integration boundaries with Workday and other enterprise applications, ensuring clear ownership across systems.
- Partner with engineering and ML teams on data quality, reconciliation,



entity resolution, and human-in-the-loop workflows.
- Maintain and govern the enterprise source-system inventory, data flows, dependencies, and outstanding architecture decisions.
- Evaluate architecture options, document trade-offs, and communicate recommendations effectively to business stakeholders, SMEs, SI partners, and senior leadership.
- Provide technical direction to distributed engineering teams and ensure architecture standards are consistently implemented.

Required Technical Skills

- 8+ years of experience in data architecture, solution architecture, or enterprise data engineering.
- Deep hands-on Databricks experience, including:
- Unity Catalog
- Lakeflow Connect & Declarative Pipelines
- Delta Lake
- Lakehouse / Medallion Architecture
- Lakebase
- Metric Views
- Lakehouse Federation
- Strong expertise in data modelling, including canonical, dimensional, relational and enterprise data models.
- Expert-level SQL and robust understanding of data structures, transformations, relationships, and data quality.
- Hands-on experience with SnapLogic or equivalent iPaaS platforms, including connector/Snap configuration.
- Strong understanding of data ingestion patterns for APIs, databases, SaaS applications, and file-based sources.
- Experience designing REST APIs / external data interfaces and data-serving architectures.
- Strong understanding of data governance, security, access control,



metadata, and lineage.

Good to Have

- Experience with Workday integrations, including EIB, RaaS, Orchestrate, or Studio.
- Understanding of entity resolution / record linkage and data matching approaches.
- Experience working with Finance data domains, including GL, Chart of Accounts, payroll, tax, treasury, or vendor data.
- Experience with VMS / contingent workforce platforms such as SAP Fieldglass, Coupa, Beeline, or Workday VNDLY.
- Experience with ML/AI data platforms and feature-serving architectures.

What We're Looking For

- A builder-architect, not a slide-deck-only architect.
- Strong ability to translate business requirements into scalable data architecture and models.
- Ability to make pragmatic architecture decisions and clearly articulate trade-offs and rationale.
- Strong stakeholder management and communication skills, including the ability to explain complex technical concepts to non-technical audiences.
- Experience providing technical direction to distributed/offshore engineering teams.
- Strong ownership mindset with the ability to drive architecture decisions from design through implementation.

Key Outcomes In the first 6 months, you will be expected to:

- Establish and govern the Databricks Lakehouse architecture and Bronze/Silver/Gold framework.
- Define and document ingestion strategies and source-to-target mappings across the systems in scope.
- Establish robust data modelling and conformance standards.
- Drive Unity Catalog governance, data access, and serving architecture.
- Establish clear integration boundaries with Workday and other enterprise systems.
- Enable engineering and ML teams to build scalable, production-ready data solutions.

📌 Databricks Solutions Architect – Data Architecture & Modelling (India)
🏢 GrowthArc
📍 India