Senior Databricks Data Engineer

First Soft Digital Solutions; Hyderabad, Chennai District, Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

First Soft Digital Solutions is seeking a Senior Databricks Data Engineer in India (Bangalore/Chennai/Hyderabad). You will drive data engineering initiatives, architect scalable pipelines, and deliver production-grade Databricks solutions across multiple cloud platforms.

10+ years in data engineering and analytics are expected. You will collaborate with data science teams, implement CI/CD practices, and optimize performance for large-scale data workloads while leading technical discussions

Qualifications

• 10+ years of experience in Data Engineering and Analytics.
• Proven Databricks delivery across architecture, development and production deployment.
• Strong knowledge of Spark architecture and large-scale data processing.
• Experience with two or more major clouds (AWS/Azure/GCP).
• Understanding of Databricks platform features and governance.

Responsibilities

• Deliver Databricks data engineering projects from design to production.
• Architect and implement scalable data pipelines and data platform components.
• Lead production deployments and CI/CD automation for data solutions.
• Collaborate with Data Science and ML teams to enable end-to-end workflows.

Skills

Databricks

Apache Spark

CI/CD

DevOps

MLOps

Cloud platforms

Data engineering

Data platforms

Analytics

Leadership

Tools

AWS

Azure

GCP

Job description

Position: Senior Databricks Data Engineer
Employment Type: Full Time
Locations: Bangalore / Chennai / Hyderabad

• 10+ years of experience in Data Engineering, Data Platforms, and Analytics, with 10+ years of overall consulting experience in enterprise technology environments.
• Strong hands-on experience with Databricks, having delivered 7-10+ data engineering projects involving architecture, development, implementation, and production deployment.
• Possess a Data Engineering Professional certification along with the required training/classes and demonstrate strong practical application of data engineering principles.
• Strong expertise in Apache Spark and distributed computing, including a solid understanding of Spark architecture, runtime internals, optimization, and large-scale data processing.
• Hands-on experience with two or more major cloud platforms AWS, Azure, or GCP, with deep expertise in at least one cloud ecosystem.
• Demonstrate strong knowledge of the Databricks platform and its broader product capabilities, including data engineering, analytics, governance, and modern data platform features.
• Experience implementing CI/CD pipelines and DevOps practices for automated testing, deployment, release management, and product ionization of data engineering solutions.
• Working knowledge of MLOps concepts and practices, with the ability to collaborate effectively across Data Engineering, Data Science, and Machine Learning teams.
• Strong understanding of performance optimization, scalability, cost optimization, and tuning of Databricks and Spark workloads for enterprise-scale data platforms.
• Excellent consulting, problem-solving, stakeholder management, and communication skills, with the ability to independently lead technical discussions and deliver complex data engineering solutions across distributed teams.

Note: Professional certification will be an added advantage.