Module Lead

Data Warehouse Developer – Databricks (Residential & MSR Domain)

Role Overview

An experienced Data Warehouse Data Engineer with strong expertise in Databricks Lakehouse architecture to join the Mphasis Data Platform team.

The role focuses on designing, developing, and optimizing data pipelines, data models, and governance frameworks for Residential (Resi) & Mortgage Servicing Rights (MSR) data warehouse initiatives. The ideal candidate combines strong Databricks engineering skills with good to have on mortgage data domain knowledge, and can collaborate with cross-functional teams to deliver high-quality, governed, and scalable solutions. Note that the Databricks flavor used in Azure Databricks

Key Responsibilities

• Data Ingestion & Processing
• Develop scalable, metadata-driven ingestion pipelines using PySpark / Spark SQL in Databricks.
• Automate batch and streaming ingestion from servicer files and internal systems.
• Handle structured/unstructured data (loan tapes, CSV, JSON, parquet, Delta Lake).
• Data Modeling & DWH Build
• Design and implement canonical data models aligned to MISMO standards.
• Build fact and dimension tables in Delta Lake with SCD handling, partitioning, Z-ordering, and performance tuning.
• Ensure model extensibility for multiple servicers and future MSR enhancements.
• Optimization & Performance
• Optimize pipelines for performance and cost (DBU management, caching, cluster configs, partition strategies).
• Implement job monitoring, logging, and ing for proactive issue resolution.
• Collaboration & Delivery
• Work with Data Architects, Governance Officers, and Business Analysts to align technical delivery with business rules.
• Follow CI/CD practices (Dev → QA → Prod migration) using Databricks Repos, GitHub, and Azure DevOps.
• Participate in code reviews, design walkthroughs, and audits to ensure compliance with standards.

• Technical skills
• 5–10+ years of experience in Data Engineering / DWH development.
• Hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog).
• Strong SQL expertise (T-SQL and SparkSQL) for data transformations and analytics – the Data Engineer might need to reverse engineer quite a few SQL SPs.
• Exposure to Delta Live Tables (DLT), streaming pipelines, and structured streaming.
• Experience with Azure Data Lake (OneLake/ADLS) as storage layer.
• Knowledge of Azure DevOps/GitHub for version control & CI/CD.
  

Nice to Have

• Experience with Power BI integration (datasets, reports on top of Databricks DWH).
• Exposure to GenAI/ML integration with Databricks for advanced analytics.
  
  

Equal Opportunity Employer

Mphasis is an equal opportunity/affirmative action employer. We provide equal employment opportunities to applicants and existing associates and evaluate qualified candidates without regard to race, gender, national origin, ancestry, age, color, religious creed, marital status, genetic information, sexual orientation, gender identity, gender expression, sex (including pregnancy, breast feeding and related medical conditions), mental or physical disability, medical conditions military and veteran status or any other status or condition protected by applicable federal, state, or local laws, governmental regulations and executive orders. View the EEO in the law poster here, view the EEO in the law supplement here. To view the pay transparency nondiscrimination provision please click here and to view the E-Verify posting click here.

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