Databricks Architect

About the role

We are looking for a Databricks Architect to lead the delivery of data engineering solutions in a client‑facing environment. This hands‑on leadership role involves working directly with clients, including C‑level stakeholders, to design, build, and deploy production‑grade Databricks platforms.

Key responsibilities

• Design and architect scalable Databricks‑based solutions for enterprise clients.
• Lead end‑to‑end cloud data platform implementations across AWS and/or Azure.
• Build production pipelines using Databricks Workflows and Spark Declarative Pipelines.
• Develop scalable ETL/ELT pipelines with Spark, PySpark, and Databricks Workflows.
• Partner with client stakeholders to translate business needs into technical solutions.
• Provide technical leadership and guidance to data‑engineering teams.
• Implement CI/CD pipelines and infrastructure‑as‑code for Databricks resources.
• Drive collaborative development through Git workflows, pull requests, and code reviews.
• Collaborate cross‑functionally with analytics, engineering, and business teams.
• Serve as the primary technical point of contact for clients, including C‑level executives.

Required profile

• 6+ years of experience in Data Engineering, Cloud Architecture, or related roles.
• 3+ years of hands‑on experience with Databricks.
• Strong proficiency in PySpark, Spark SQL, Python, and SQL.
• Deep experience with Delta Lake, Unity Catalog, Delta Live Tables, and Databricks Jobs.
• Proven experience delivering Databricks projects in a consulting or professional services environment.
• Strong understanding of data‑lake concepts and formats (Delta, Iceberg, Parquet, etc.).
• Experience designing and managing Unity Catalog for governance, access control, and lineage.
• Familiarity with medallion architecture (bronze/silver/gold) patterns.
• Hands‑on experience with Git version control, pull requests, code reviews, and collaborative development workflows.
• CI/CD and infrastructure‑as‑code experience for Databricks resources (Terraform, Asset Bundles, GitHub Actions).
• MLflow experience: experiment tracking, model registry, deployment, and observability.
• Cloud platform experience (AWS, Azure).
• Experience working in client‑facing, consulting, or cross‑functional environments.
• Experience leading technical projects or mentoring engineering teams.

Required skills

• Databricks
• PySpark
• Spark SQL
• Python
• SQL
• Delta Lake
• Unity Catalog
• Terraform
• Git
• MLflow
• AWS
• Azure

What we offer

• Constant opportunities for exposure and learning.
• Flexible working location supporting personal‑life harmony.
• Agency and influence in the company’s overall strategy.
• Collaboration with a high‑performing team.
• Competitive base salary and target bonus of 15‑25%.
• 401k, healthcare benefits, paid time‑off, and more.