Architect

Area(s) of responsibility

Job Title: Databricks Architect

Location: Noida or Pune

Experience: 10+ years (with 3–5 years in Databricks / Spark ecosystem)

Role Overview

We are looking for a highly skilled and experienced Databricks Architect with technical expertise and strong client-facing capabilities. This role requires hands-on leadership in designing and implementing scalable data platforms using Databricks and modern data engineering practices, while actively engaging with customers to understand business needs, define solutions, and drive successful delivery.

 

Key Responsibilities

Architecture & Solution Design

•            Design and implement end-to-end data platforms using Databricks (Lakehouse architecture).

•            Define data ingestion, transformation, and serving layers for batch and real-time pipelines.

•            Architect scalable solutions using Delta Lake, Unity Catalog, and MLflow.

•            Ensure data governance, security, and compliance across the platform.

Hands-on Development

•            Develop and optimize data pipelines using PySpark, SQL, and Databricks notebooks.

•            Implement performance tuning, cost optimization, and workload management strategies.

•            Build reusable frameworks for data processing, orchestration, and monitoring.

 

Customer Engagement

•            Act as a trusted advisor to clients, translating business requirements into technical solutions.

•            Lead workshops, discovery sessions, and architecture discussions with stakeholders.

•            Present solution approaches, trade-offs, and roadmaps to business and technical audiences.

•            Provide guidance on best practices, governance models, and platform adoption.

Delivery & Leadership

•            Lead technical teams and provide mentorship to data engineers.

•            Drive solution delivery, code quality, and DevOps best practices (CI/CD, testing).

•            Collaborate with cross-functional teams (Data Science, BI, DevOps, Cloud).

•            Support pre-sales activities including solutioning, estimations, and proposals.

 

Required Skills & Qualifications

Technical Skills

•            Strong experience with Databricks Lakehouse Platform.

•            Expertise in Apache Spark (PySpark/Scala), SQL.

•            Hands-on experience with Delta Lake, Unity Catalog, MLflow.

•            Experience with cloud platforms: Azure.

•            Strong understanding of data architecture patterns (medallion architecture, data mesh).

•            Experience with data orchestration tools (ADF, Airflow, etc.).

•            Knowledge of data security, RBAC, and governance frameworks.

 

Customer-Facing Skills

•            Strong communication and presentation skills.

•            Experience in client interactions, requirement gathering, and stakeholder management.

•            Ability to simplify complex technical concepts for business users.

 

Good to Have

•            Experience in the Insurance domain (Claims, Underwriting, Policy Administration, Reinsurance).

•            Exposure to GenAI / LLM use cases on Databricks.

•            Certifications in Databricks / Azure / AWS.