Principal Software Engineering Manager - Data Science & Engineering

Microsoft•Redmond, WA

About The Position

The Cloud & AI organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. Microsoft is one of the largest enterprise service companies in the world. The MSRC Data Science team is responsible in building data pipelines, data mining, ML models and insights on security related data. We combine our data science work with business and engineering knowledge to provide unique insights into customer scenarios that are leading the data-driven culture within security. We hire people with a desire to build great products and make business impact using data analysis, machine learning, experiments, data mining, data visualization, and more. We welcome applications from diverse multi-disciplinary backgrounds, with analytical skills, engineering abilities, communication skills, business interests, relentless curiosity, and a desire to improve the experiences of more than one billion customers. We are looking for a Principal Software Engineering Manager - Data Science & Engineering to join our team! 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. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience.
4+ years people management experience.
Expereince guiding the the architecture of scalable pipelines and datasets.
Experience leading teams to build and operate machine learning and data extraction, transformation, and loading (ETL) pipelines.

Responsibilities

Leads team on the disciplined use of, and improving artificial intelligence (AI) tools and practices across the software development lifecycle (SDLC). Guides team on proactively taking responsibility for the content of their AI-generated requirements, design documents, code, and other assets, and assisting other members of the team to do the same. Leads team on incorporating Responsible AI practices into the SDLC to ensure appropriate controls over AI-generated assets.
Coaches team on applying SDLC and engineering health measures (e.g., Accelerate, SPACE framework, Engineering System Success Playbook [ESSP]) to guide improvements to processes and practices, especially those involving AI. Leads team on experimenting with AI tools and practices to improve their own capabilities, and providing recommendations on how to adopt them to others.
Reviews debugging tools, tests, logs, telemetry, and other methods, and acts as an expert for others to proactively verify assumptions while developing code before issues occur across products in production
Guides team to perform machine learning/data extraction, transformation, and loading (ETL) pipelines (e.g., data collection, cleaning) based on data prepared. Guides the architecture of scalable pipelines and datasets. Influences the direction of the team. Begins to anticipate potential data pipeline issues and provides solutions. Collaborates with data providers across disciplines. Guides team to use data pipelines for training, as well as for shipping models which should execute correctly.
Conducts incident retrospectives to identify root causes of problems, and leads teams on implementing repair actions and identifying mechanisms to prevent incident recurrence. Tracks and attempts to minimize cost of debugging multiple scenarios. Leads team on proactively applying least-access principles, using logging, telemetry, and other appropriate mechanisms to investigate issues while retaining privacy and security, and driving those practices.
Guides team within and across teams on producing extensible, maintainable, well-tested, secure, and performant code that adheres to design specifications. Leads efforts to continuously improve code performance, testability, maintainability, effectiveness, and cost, while learning about and accounting for relevant trade-offs. Identifies best practices and coding patterns and provides deep expertise on the coding and validation strategy.
Defines or reuses quality metrics, best practices, and coding patterns to ensure testable code. Leads by example in best code-writing practices (e.g., leveraging state-of-the-art generative artificial intelligence [GenAI], approaches to source code organization, naming conventions). Leads team on identifying and anticipating blockers or unknowns during the development process, escalating them, communicating how they will impact timelines, and leading efforts to identify and implement strategies and/or opportunities to address them.
Guides team on leading the identification of requirements for, and the comprehensive application of automation within production and deployment across products, targeting zero-touch deployment when possible. Guides others to run code in simulated, or other non-production environments to confirm functionality and error-free runtime across products. Ensures a continuous integration/continuous deployment (CICD) infrastructure is in place that promotes developer and operational agility (e.g., low lead-time-to-change metrics).
Guides team on driving multiple groups' project plans, release plans, and work items in coordination with appropriate stakeholders (e.g., technical program managers). Breaks down very long-term project vision into milestones. Guides other members on project estimation. Anticipates future goals to guide future resources. Reviews, implements, and recommends updates to resource management in response to changing context. Guides team on driving efforts to ensure required security protections and detection processes are accounted for in planning. Guides team on driving efforts to ensure project plans adhere to security, privacy, and compliance requirements.
Guides team on driving efforts to ensure all code for a set of products/solutions is properly flighted for quicker mitigation of production incidents. Leads team on calculating adequate capacity for planning, accounting for appropriate failover and backup/restore mechanisms for disaster recovery for a set of products