Xpedient Technologies, LLC

Informatica MDM and Databricks Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Informatica MDM and Databricks Engineer, offering a remote contract for over 6 months at a competitive pay rate. Requires a Bachelor's degree, 7 years of data engineering experience, and expertise in Informatica MDM and Databricks.
🌎 - Country
United States
πŸ’± - Currency
Unknown
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
March 6, 2026
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
Remote
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Texas
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🧠 - Skills detailed
#PySpark #"ETL (Extract #Transform #Load)" #Leadership #Data Management #AI (Artificial Intelligence) #Data Architecture #Delta Lake #Data Pipeline #Data Science #Compliance #SQL (Structured Query Language) #Cloud #Security #Data Access #Azure #Data Engineering #Migration #Cybersecurity #AWS (Amazon Web Services) #API (Application Programming Interface) #Strategy #Databricks #Data Quality #Computer Science #Spark (Apache Spark) #Data Stewardship #Informatica #REST (Representational State Transfer) #Data Strategy #MDM (Master Data Management) #ML (Machine Learning)
Role description
Job Summary Performs highly advanced (senior-level) data architecture and engineering work. This role is responsible for designing, implementing, and maintaining the Master Data Management (MDM) ecosystem. You will serve as the technical lead in integrating disparate data sourcesβ€”ranging from the Offender Management System to Financial and HR recordsβ€”into a unified Databricks Lakehouse. Using Informatica IDMC/MDM, you will ensure the integrity and security of the "Golden Record" to support critical agency decision-making and public safety reporting. Essential Functions MDM Hub Strategy: Design and configure Informatica MDM components (Hub Console, Match/Merge rules, Trust Frameworks, and Hierarchy Management) to resolve identities across legacy mainframe and modern SQL environments. Databricks Lakehouse Integration: Lead the development of Spark-based ETL/ELT pipelines in Databricks to ingest large-scale agency data into Delta Lake (Medallion Architecture), ensuring MDM-cleansed data is available for downstream AI/ML and analytics. Data Quality & Governance: Implement automated data quality (DQ) checks using Informatica CDQ and Databricks Unity Catalog to maintain strict compliance with Texas cybersecurity and CJIS (Criminal Justice Information Services) standards. Modernization Leadership: Support the transition of legacy data systems into the SITS corrections infrastructure, ensuring that master data remains consistent during large-scale system migrations. API & Interoperability: Develop and maintain REST/SIF APIs to provide real-time master data access to operational systems (e.g., inmate banking, parole tracking). Technical Consultation: Provide subject matter expertise to the Data Management Office (DMO) and collaborate with the Chief Data Officer on the agency’s long-term data strategy. Required Minimum QualificationsEducation & Experience Degree: Bachelor's degree from an accredited college or university in Computer Science, MIS, or Data Science. (Experience may substitute for education on a year-for-year basis). Experience: β€’ Seven (7) years of full-time data engineering or architecture experience. Three (3) years of hands-on experience with Informatica MDM (10.x or IDMC). Two (2) years of experience building data pipelines in Databricks (PySpark/SQL). Preferred: Previous experience with State of Texas agencies or Public Safety data. Technical Skills Master Data Management: Deep knowledge of Hub configuration, survivorship logic, and data stewardship workflows. Cloud Architecture: Proficiency in Azure or AWS cloud environments as they relate to Databricks and Informatica IDMC. Security & Compliance: Understanding of CJIS security policies and the Texas Responsible AI Governance Act. Legacy Systems: Familiarity with integrating data from IBM Mainframe/DB2 or legacy flat files is a major plus. Work Location: Remote