Databricks Engineer

Ergobite; Maharashtra; On-site; INR 3,500,000 - 7,500,000; Full time

Job summary

Ergobite in Maharashtra, India, is seeking a highly skilled Databricks professional with 6-10 years of hands-on experience to design, implement, and optimize data solutions.

You will architect scalable pipelines using Spark, Delta Lake, MLflow, and cloud platforms, mentor engineers, and collaborate with stakeholders to deliver measurable outcomes.

This role favors an independent contributor who communicates clearly and can grow into a practice lead as the team expands.

Qualifications

• 6–10 years of Databricks experience with end-to-end delivery.
• Strong Spark, Delta Lake and cloud data engineering expertise.
• Excellent communication and stakeholder management.
• Independent, self-driven contributor with leadership potential.
• Experience mentoring or leading small teams.
• Exposure to AI/ML workflows with MLflow.
• Familiarity with data governance, security, and compliance.
• Problem-solving with a consultative approach.

Responsibilities

• Architect, develop, and optimise scalable data pipelines, ETL workflows and analytics using Databricks.
• Deliver production-grade implementations across Spark, Delta Lake, MLflow and Databricks SQL.
• Mentor junior engineers and help establish best practices.
• Collaborate with stakeholders to translate business requirements into technical solutions.
• Stay ahead of Databricks features and industry trends to propose forward-looking solutions.

Skills

Databricks

Apache Spark

Delta Lake

MLflow

Cloud data engineering

Tools

Databricks

Spark

Delta Lake

MLflow

Job description

We are seeking a highly skilled Databricks professional with 3-5 years of hands‑on experience in designing, implementing, and optimising data solutions. This role is ideal for an independent contributor who thrives in dynamic environments, communicates with clarity, and has the vision to help build and mentor a growing team around them.

Responsibilities

• Databricks Solutions: Architect, develop, and optimise scalable data pipelines, ETL workflows, and advanced analytics solutions using Databricks.
• Hands‑on Engineering: Deliver production‑grade implementations across Spark, Delta Lake, MLflow, and Databricks SQL.
• Team Building: Act as a cornerstone for the practice, mentoring junior engineers and helping establish best practices.
• Client Engagement: Collaborate with stakeholders to translate business requirements into technical solutions with measurable outcomes.
• Innovation: Stay ahead of emerging Databricks features and industry trends to propose forward‑looking solutions.

Requirements

• 6‑10 years of Databricks experience with proven delivery of end‑to‑end solutions.
• Strong expertise in Apache Spark, Delta Lake, and cloud‑native data engineering (Azure/AWS/GCP).
• Excellent communication skills, ability to explain complex technical concepts to non‑technical stakeholders.
• Independent, self‑driven, and outcome‑focused individual contributor.
• Experience mentoring or leading small teams, with potential to scale into a practice lead role.
• Exposure to AI/ML workflows using MLflow or similar frameworks.
• Familiarity with data governance, security, and compliance in enterprise environments.
• Strong problem‑solving mindset with a consultative approach.