Data Engineer
Work Arrangement
Office Days per Week: 2 days
Key Skills
Job Description
We are currently hiring a Databricks Data Engineer for an exciting client engagement. Role: Databricks Data Engineer Location: Hybrid(2 days a week) Position: Contract Language : Fluent English Role Summary We are looking for an experienced Databricks Data Engineer to build scalable master data and integration solutions on a modern Databricks Lakehouse. The role will focus on common IDs, Golden Records, entity resolution, data quality, governance, and cross-platform data integration. Experience: 6–10+ Years Key Skills: MDM, Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Data Quality, Data Governance Key Responsibilities Design and implement MDM solutions, including common IDs, Golden Records, entity matching, deduplication, and survivorship rules. Integrate data from multiple source systems into the Databricks Lakehouse Develop and optimize data pipelines using Databricks, PySpark, SQL, and Delta Lake. Build and enhance Bronze, Silver, and Gold data layers. Implement data quality, standardization, reconciliation, and validation processes. Support Unity Catalog, data lineage, access controls, cataloguing, and data governance. Implement data masking and anonymization for sensitive data. Build trusted, reusable data layers for cross-platform analytics and intelligence. Collaborate with business, architecture, and engineering teams to define MDM and data integration requirements. Required Skills Strong experience in data engineering. Hands-on expertise in Databricks, PySpark, SQL, Delta Lake, and Lakehouse architecture. Experience with Golden Records, common IDs, entity resolution, deduplication, and data quality. Good understanding of Unity Catalog, data governance, metadata, and lineage. Experience integrating data from multiple enterprise platforms. Knowledge of Medallion Architecture and data privacy/anonymization. Good to Have Experience with Informatica MDM/IDMC, Reltio, Profisee, Semarchy, or similar MDM platforms. Cloud experience with Azure, AWS, or GCP. Exposure to large-scale data modernization or migration programs.
Core Responsibilities
Design and build master data management and integration solutions on Databricks, including common IDs, Golden Records, entity resolution, data quality, and scalable Bronze, Silver, and Gold data layers. Integrate enterprise data sources, implement governance and privacy controls, and collaborate with business, architecture, and engineering teams to define requirements.
Requirements
Requires 6–10+ years of data engineering experience and hands-on expertise in Databricks, PySpark, SQL, Delta Lake, and Lakehouse architecture. Candidates should have experience with master data management, entity resolution, data quality, Unity Catalog, governance, enterprise data integration, and data privacy; experience with MDM platforms and a major cloud provider is advantageous.
About Response Informatics
Industry: IT Services and IT Consulting
Company size: 51-200 employees
Response Informatics is a globally established end-to-end technology and enterprise-level management consulting company. We have our corporate offices in New Jersey, USA, and Hyderabad, India. Incorporated in 1996, we have been sailing the ship with a single goal, the global adaption of the best technological and result driven practices for business growth. With a humble start with management consulting and global staffing solutions, we have moved up the ladder sharply and significantly. Soon enough, we were delivering in various verticals and services ranging from enterprise level software and application development. From mere technological consultation to high end, in-depth Centres of Excellence for cutting edge technologies such as Blockchain, Artificial intelligence, Data analytics, Robotic Process Automation, Internet of Things. Every aspect of the technology dealt in and every service undertaken is entirely consumer-centric data-driven and most importantly, has its fundamentals dug deep into our result oriented strategies or ideologies.