Databricks Engineer

• Design and build new tools and engines using Python, PySpark, and Databricks .
• Maintain, upgrade, and migrate existing engines, including legacy stored procedures.
• Develop and enhance data pipelines and automation workflows.
• Analyze and process source data and modify or transform engine logic as required.
• Support quality measure and rule development, including clinical measures.

• Collaborate with onshore and offshore teams., The Databricks Architect will be responsible for designing, implementing, and governing enterprise-scale data platforms on Databricks. The role focuses on data architecture, cloud integration, data engineering best practices, analytics enablement, and platform optimization across Azure, AWS, or Google Cloud Platform. Responsibilities

• Design and implement scalable data lakehouse architectures using Databricks.
• Define enterprise data models, governance standards, and security controls.
• Lead migration of legacy data warehouses and ETL workloads to Databricks.
• Architect batch and real-time data processing solutions using Spark.
• Optimize performance, scalability, reliability, and cost efficiency.
• Collaborate with business stakeholders, data engineers, data scientists, and cloud architects.
• Establish CI/CD, monitoring, and operational best practices.
• Provide technical leadership and mentor engineering teams.

We are hiring for 2 positions under one posting . Please review the requirements below and share only relevant profiles., * Strong hands-on programming experience and ability to build solutions independently.

• Deep experience with Python and PySpark Mandatory .
• Working experience with Databricks .
• Strong experience with stored procedures and legacy-to-modern migration.
• Strong understanding of data and ability to interpret and transform data.
• Healthcare data, clinical quality measures, or rule development experience strongly preferred., * 8+ years of data engineering and data platform experience.
• 3+ years of hands-on Databricks architecture experience.
• Strong expertise in Apache Spark, PySpark, SQL, and Delta Lake .
• Experience with Azure Databricks, AWS Databricks, or Google Cloud Platform Databricks .
• Strong expertise in Google Cloud Platform Pub/Sub, Azure Event Hubs, AWS Kinesis, or Apache Kafka .
• Experience with producer/consumer architecture decisions and trade-offs.
• Knowledge of data lakehouse architecture and data governance.
• Experience with data integration tools and orchestration frameworks.
• Strong understanding of security, access management, and compliance requirements.

Preferred Skills

• Databricks Certified Data Engineer Professional or equivalent.
• Experience with Unity Catalog, Delta Live Tables, and Databricks Workflows.
• Experience with Power BI, Tableau, or other BI platforms.
• Knowledge of DataOps, DevOps, and MLOps practices., Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field. Master’s degree preferred. Please mention the position you are submitting the candidate OR when sharing the profile/Resume