Senior Data Modeler Data Engineer (MongoDB & Azure)

Brief Role Summary
This role supports an Enterprise Payments operational data store and cloud-based analytics platform with a balanced focus on JSON/MongoDB data modeling and cloud data engineering. The role partners closely with data analytics and payments stakeholders to onboard new data pipelines improve data quality and ensure compliance with enterprise governance standards.

Must-Have Skills
MongoDB & JSON Data Modeling: Strong hands-on experience designing JSON/XSD/JSON schemas managing schema evolution versioning and migration strategies with a focus on performance and data quality.

Azure Data Engineering: Advanced SQL and PySpark (Spark SQL performance tuning) with hands-on experience in Azure Databricks Azure Data Factory (ADF) and Azure Synapse for ingestion and curation pipelines.

Governance & Stakeholder Collaboration: Proven ability to work with business and analytics partners translate requirements into scalable data solutions and ensure adherence to governance privacy and metadata standards.

Job Description

• Design and maintain JSON-based data models that support business workflows and optimize query patterns for both transactional and analytical use cases.
• Lead MongoDB schema evolution including versioning backward compatibility and migration strategies aligned with changing data requirements.
• Apply best practices for indexing partitioning/sharding and performance optimization across MongoDB collections.
• Build and maintain data ingestion and curation pipelines using Azure Databricks Azure Data Factory and Azure Synapse.
• Develop and optimize PySpark pipelines for scale performance and cost efficiency within cloud environments.
• Collaborate with analytics teams and business stakeholders to curate high-quality datasets for downstream reporting and analytics.
• Ensure end-to-end compliance with enterprise data governance standards including privacy access controls metadata management and audit readiness.