Position : Databricks Architect

Overall/Total Experience : 5-9 years

Location : Bengaluru

Working Days : 5 Days Working from Office

Notice Period Requirement : 60 Days (Maximum)

Client's Company Size : Startup/Small Enterprise

Certification Requirement :

- Must hold at least one active Databricks Professional-level certification (Data Engineer Professional preferred).

Roles & Responsibilities :

- Translate client requirements into Databricks-based solution designs - data pipelines, Lakehouse layouts, and serving layers.

- Recommend the right Databricks components (Delta Live Tables, Workflows, Unity Catalog, Databricks SQL, Genie) for a given use case, based on data volume, latency, and governance needs.

- Participate in pre-sales and proposal discussions, contributing effort estimates and technical approach for Databricks-based engagements.

- Build and maintain end-to-end pipelines : ingestion (Auto Loader, DLT), transformation (dbt or native PySpark/SQL), and serving (Unity Catalog, Databricks SQL).

- Work directly with pharma commercial datasets - IQVIA, Symphony, CRM, Hub/SP, claims - modeling them into clean, governed Delta Lake structures.

- Develop and maintain reusable components : notebooks, job templates, SQL libraries, and data quality checks.

- Configure and tune Genie Spaces and AI/BI dashboards for client-facing analytics use cases.

- Contribute to and maintain internal Databricks standards, templates, and knowledge base.

- Support the certification and upskilling of junior engineers and analysts on the team.

- Help establish the Databricks practice - codifying reusable design patterns, reference architectures, and coding standards.

- Design and build solution accelerators for common pharma use cases (prescription analytics, patient cohort analysis, omnichannel attribution) that can be reused and adapted across clients.

Candidate Requirements :

- Must have 5+ years in Data engineering/Data architect roles, with at least recent 3 years of hands-on Databricks experience.

- Must be able to design a solution end-to-end and then build it themselves.

- Must have experience translating client/business requirements into Databricks solution designs - data pipelines, Lakehouse layouts, and serving layers.

- Must have built and maintained end-to-end pipelines - ingestion (Auto Loader, DLT), transformation (PySpark/SQL or dbt), and serving (Unity Catalog, Databricks SQL).

- Must hold at least one active Databricks Professional-level certification (Data Engineer Professional preferred).

- Must have solid working knowledge across the Databricks stack - Delta Lake, Delta Live Tables, Unity Catalog, Auto Loader, Databricks SQL, Workflows, and cluster/job configuration.