About The Role We are looking for an experienced Databricks Engineer with 12+ years of overall IT experience to join our team on a long-term contract. The ideal candidate should have deep expertise in Databricks, Apache Spark, PySpark, Python, SQL, and cloud platforms (AWS, Azure, or GCP), along with a proven track record of delivering enterprise-scale data engineering solutions. This is a customer-facing role requiring strong technical leadership, solution architecture capabilities, and hands-on experience building scalable cloud-based data platforms.

Mandatory Certification Databricks Certified Data Engineer Professional (Mandatory) Key Responsibilities Lead end-to-end Databricks implementation projects from solution design through deployment and production support.

Design, develop, and optimize scalable data pipelines using Databricks, Apache Spark, and PySpark.

Build cloud-native data engineering solutions using AWS, Microsoft Azure, or Google Cloud Platform (GCP).

Design and implement modern Lakehouse architectures for enterprise-scale data platforms.

Translate business requirements into scalable, high-performance technical solutions.

Integrate Databricks solutions with enterprise applications, APIs, and third-party systems.

Configure, monitor, troubleshoot, and optimize Databricks environments for performance, reliability, and scalability.

Implement CI/CD pipelines and DevOps best practices for data engineering workflows.

Collaborate with architects, business stakeholders, and cross-functional teams to deliver high-quality solutions.

Provide technical leadership, mentor engineering teams, and promote best practices.

Participate in customer workshops, architecture discussions, and technical consulting sessions.





Ensure solution quality, security, governance, and operational excellence throughout project delivery.

Required Skills Databricks

Apache Spark

PySpark

Python

SQL

Data Engineering

ETL/ELT Pipeline Development

Lakehouse Architecture

AWS / Microsoft Azure / Google Cloud Platform (GCP)

Solution Architecture

Systems Integration

CI/CD Pipelines

Performance Optimization

Data Modeling & Data Warehousing

MLOps

Git & DevOps Practices Required Experience 12+ years of overall IT experience.

Hands-on expertise with Databricks and modern data engineering platforms.

Experience delivering 10+ end-to-end Databricks implementation projects.

Strong experience with distributed data processing using Apache Spark and PySpark.

Proven experience designing and implementing enterprise-scale cloud-based data platforms.

Strong understanding of Lakehouse Architecture, data integration, governance, and data modeling.

Experience implementing CI/CD pipelines and deployment automation.

Excellent troubleshooting, debugging, and performance tuning skills.

Solid client-facing consulting and stakeholder management experience.

Preferred Qualifications Experience with Delta Lake, Unity Catalog, MLflow, and Databricks Workflows.

Knowledge of up-to-date data architecture patterns and cloud-native services.

Experience working in Agile/Scrum environments.

AWS, Azure, or GCP certifications are an added advantage.

Soft Skills

Excellent communication and presentation skills.

Strong analytical and problem-solving abilities.

Customer-first mindset with strong consulting skills.

Ability to manage multiple priorities in a fast-paced environment.

Leadership, ownership, and mentoring capabilities.

📌 Databricks Engineer (Gurugram)
🏢 Impronics Technologies
📍 Gurugram