Tech Lead - Databricks

Job Summary

Tech Lead, Databricks Modern Data Stack. Company: Creole Studios. Location: Ahmedabad, India. Reports to: Founder CEO. Type: Full-time.

About the role Creole Studios is launching a dedicated Data AI practice focused on the modern data stack, with Databricks as the anchor. The target market is US mid-market companies that need data platforms that actually work in production. We are hiring our first Tech Lead for this practice. You will be one of the first engineers on the ground, lead a small pod of data engineers, and own technical delivery on our early client engagements. This is a hands-on lead role. Roughly 60% deep technical work (architecture, code, reviews), 30% team leadership (mentoring, planning, quality), 10% client and pre-sales support. If you are a strong senior data engineer ready for a lead role with real ownership, this is the seat.

Responsibilities

• Technical delivery: Architect and build Databricks-based data platforms for US mid-market clients. Design and implement medallion architectures, Delta Lake pipelines, Unity Catalog governance, and Workflows-based orchestration. Write production PySpark and SQL. Yes, you will still be in the code. Set engineering standards: code quality, testing, CI/CD, IaC, monitoring. Own technical decisions on your projects. Architecture, tooling, trade-offs.
• Team leadership: Lead a pod of 3 to 5 data engineers across 1 to 2 client engagements. Run code reviews, design reviews, and weekly technical syncs. Mentor mid and junior engineers. Help them get certified. Interview and help hire engineers into your pod.
• Client work: Be the technical point of contact for client engineering teams. Run technical workshops, requirement-gathering sessions, and architecture reviews with client stakeholders. Translate business requirements into technical solutions. Support pre-sales: scoping calls, technical proposals, effort estimates. You will not own pre-sales, but you will be in the room.
• Practice building: Contribute to internal IP: reusable accelerators, reference architectures, demo assets. Help shape engineering standards and delivery playbooks for the practice. Co-author technical blog posts and case studies.

What you bring

• Must have 6 to 10 years in data engineering, with at least 3 years on Databricks or Spark at production scale.
• Strong PySpark and SQL. You can write, debug, and optimize Spark jobs without help.
• Databricks ecosystem fluency: Delta Lake, Unity Catalog, Workflows or DLT, MLflow basics.
• Databricks Certified Data Engineer Associate or Professional (or willing to get certified within 60 days of joining).
• One cloud at strong level, ideally AWS or Azure.
• Comfortable with IAM, networking basics, and Terraform or equivalent IaC.
• Modern data stack exposure beyond Databricks: Airflow, dbt, Fivetran, or similar.
• Prior lead or senior engineer experience. You have led at least one team of 3+ engineers on a real project.
• DevOps fluency: CI/CD pipelines, Docker, Kubernetes, observability tooling.

What this role is not

• A pure individual contributor seat. You will lead people.
• A management-only role. You will still be in the codebase every week.
• A 9-to-5 with a fixed scope. Early-practice work is variable. Some weeks are heavy delivery, some are pre-sales support, some are internal RD.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.