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.
- Strong client-facing consulting and stakeholder management experience.

Preferred Qualifications

- Experience with Delta Lake, Unity Catalog, MLflow, and Databricks Workflows.
- Knowledge of modern 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 robust consulting skills.
- Ability to manage multiple priorities in a fast-paced environment.
- Leadership, ownership, and mentoring capabilities.

📌 Databricks Engineer (India)
🏢 IMPRONICS DIGITECH PRIVATE
📍 India