Software Engineering II

Microsoft•Redmond, WA

About The Position

Commerce + Ecosystems (C+E) is responsible for enabling and optimizing the end-to-end customer journey on the Microsoft Cloud. C+E’s Commerce Financial Platforms (CFP) team is responsible for Financial Platforms, Global Payments Platforms, Employee Financial Experiences, and C+E Compliance, and also develops and operates financial commerce platforms and tools that perform all revenue management functions for our customers, partners, and staff worldwide. Are you driven by the challenge of designing enterprise-scale distributed systems? Does building a cutting-edge global payments platform in a cloud-first environment motivate you? Are you ready to build compelling interfaces to bring new and innovative ways for customers to interact with our payment experiences? If you're passionate about solving complex engineering problems and delivering impact through high-quality systems, we encourage you to apply. We are the Payments engineering team within the Global Payments Platform (GPP) organization, a core platform in the Commerce & Ecosystem group at Microsoft. Our mission is to build and operate the backbone of Microsoft’s commerce capabilities—delivering seamless payment experiences, enforcing top-tier security and compliance, and ensuring high reliability and performance across global transactions. Our services support major Microsoft business units including Xbox, Office 365, Azure, Entra, Microsoft Store, and Edge, and are deployed in over 200 countries. We are looking for an experienced data engineer to develop the data strategy to shape the next generation of fintech experiences and platform capabilities for Microsoft’s ecosystem of products. As a data engineer, you will be responsible for designing and executing payment-wide data architecture. You will help to set the stage for payments to be a data-led organization and will align with product and cross functional teams, strategize, and define engagement models and surface areas to address and help us manage our business more effectively in terms of customer credit, enhanced cart performance, subscription churn rates, payment approval rates, payment anomalies, AI/Copilot models, and more. You will be part of a team that owns all current payment data models including the ingestion and processing pipelines and outputs. This strategic role will be accountable for executing on data for 1P, 3P, Cash, liquidity position, payments strategy across all Microsoft product teams such as gaming, advertising, E&D, Azure, LinkedIn, HoloLens, and GitHub, along with Microsoft CELA and Finance. The ideal candidate has a successful track record working in data engineering roles that marry user experience, platform capabilities with requirements impacting an ecommerce platform. Customer empathy, outstanding communication, excellence in distilling ambiguity, FinTech/Fin Services or ecommerce, and running complex technical and business programs in parallel are must-haves to be successful in this role that will be central around executing on an overall Microsoft Payments strategy that spans both consumer and commercial businesses. In addition to the data platform development work, the position also includes building and maintaining existing financial reconciliation solutions for Microsoft, ensuring alignment between Microsoft and its financial partners. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Nice To Haves

Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering , or related field AND 5+ years' experience in data engineering, data science, software development, or data modeling OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering or related field AND 4+ year(s) experience in data engineering or data science OR equivalent experience.
Meaningful experience in following technologies: Python, SQL
Experience and interest in Cloud platforms such as Azure (preferred) or AWS
Experience in Distributed Processing using Apache Spark, Databricks
Expert in creating data structures optimized for storage and various query patterns for e.g., Parquet and Delta Lake
Meaningful experience in at least one database technology such as:
Traditional RDBMS (MS SQL Server, Oracle)
NoSQL (MongoDB, Cassandra, Neo4J, Cosmos DB, Gremlin)

Responsibilities

Data Requirements and Modeling
Supports collaborations with appropriate stakeholders and records and documents data requirements.
Evaluates project plan to understand data costs, access, usage, use cases, and availability for business or customer scenarios related to a product feature.
Contributes to the appropriate data model for the project and drafts design specification documents to model the flow and storage of data for specific parts of a data pipeline.
Works with senior engineers and appropriate stakeholders (e.g., Data Science Specialists) to contribute basic improvements to design specifications, data models, or data schemas, so that data is easy to connect, ingest, has a clear lineage, and is responsive to work with.
Participates in code reviews and provides constructive feedback to team members.
Uses knowledge of one or more use cases to implement orchestration techniques that automate data extraction logic from one source to another.
Uses basic data protocols and reduction
Data Management and Transformation
Assesses data quality and completeness using queries, data wrangling, and basic statistical techniques.
Helps others merge data into distributed systems, products, or tools for further processing.
Designs and maintains assigned data tools used to transform, manage, and access data.
Writes efficient code to test and validate storage and availability of data platforms and implements sustainable design patterns to make data platforms more usable and robust to failure and change.
Works with others to analyze relevant data sources that allow others to develop insights into data architecture designs or solution fixes.
Operational Excellence
Follows existing documentation to implement performance monitoring protocols across a data pipeline.
Thereby improves on the current processes for metric collections and evangelizes it across the team.
Performs root cause analysis in response to detected problems/anomalies to identify the reason for alerts and implement basic solutions that minimize points of failure.
Implements and monitors improvements across assigned product feature to retain data quality and optimal performance (e.g., latency, cost) throughout the data lifecycle.
Uses cost analysis to suggest solutions that reduce budgetary risks.
Works with others to document the problem and solution through postmortem reports and shares insights with team or leadership.
Provides data-based insights into the health of data products owned by the team according to service level agreements (SLAs) across assigned features.