Databricks Engineer

Preferred (Domain) : Pharma or life sciences background

Key Responsibilities :

1. Solutioning &

• Architecture :
• 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.
• Participate in pre-sales and proposal discussions, contributing effort estimates and technical approach.
• Review architecture decisions with senior architects and flag risks or better alternatives.

2. Hands-On Build &

• Delivery :
• 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.
• Own workspace-level hygiene : cluster policies, job scheduling, cost tracking, and performance tuning.

3.

Platform

Currency &

• Best Practices :
• Stay updated with new Databricks releases and features and assess their relevance to pharma use cases.
• Bring new capabilities into existing client engagements where they create real value.
• Contribute to and maintain internal Databricks standards, templates, and knowledge base.
• Support the certification and upskilling of junior engineers and analysts.

4. Client &

• Team Collaboration :
• Act as the day-to-day Databricks technical point of contact on assigned client engagements.
• Explain technical trade-offs in plain terms to non-technical stakeholders.
• Collaborate with analytics, forecasting, and delivery teams.

5.

Practice Building :

• Help establish the Databricks practice at DataZymes - 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).
• Support partnership conversations with Databricks by contributing technical input.

Ideal Candidate :

• Strong hands-on Databricks Architect/Engineer profile with end-to-end build-and-solution capability and Databricks professional certification.
• 5+ years in Data engineering/Data architect roles, with at least 3 years of hands-on Databricks experience.
• Must be able to design a solution end-to-end and build it themselves.
• Must have experience translating client/business requirements into Databricks solution designs.
• Must have built and maintained end-to-end pipelines (ingestion, transformation, serving).
• Must hold at least one active Databricks Professional-level certification.
• Solid working knowledge across the Databricks stack (Delta Lake, DLT, Unity Catalog, Auto Loader, Databricks SQL, Workflows).
• Strong SQL and PySpark skills.
• IT services/consulting background with direct delivery on client engagements preferred.
• Stable tenure : 2+ years average per employer.
• Role is Hybrid, with WFH flexibility up to 6 days a month.

Note : CTC is inclusive of 20% variable.