Data Engineer – Construction Quality

at  Microsoft

Microsoft Cloud Operations + Innovation (CO+I) is the team behind the cloud. CO+I is responsible for delivering over 200 Microsoft web portals, Live and Online Services around the world including infrastructure, security and compliance, operations, globalization, and manageability. Our focus is on smart growth, high efficiency, and to deliver trusted experience to customers and partners worldwide.
Our datacenter delivery team is looking for a data professional to bring their skills to the construction quality space. Our team maintains and governs processes, delivers data, metrics, and analytics, and provides process automation to improve our predictability and quality in our datacenters. The Data Engineer - Construction Quality will be part of the global team and lead the data and metrics program to provide analytics and insights, automation, and drive platform maturity to our tooling, applications, and suite of visualization and reporting products.

Our ideal candidate will have:

• In-depth knowledge of the business, its data landscape, and the lineage of our data across multiple areas
• A customer- and/or stakeholder-oriented focus by understanding their needs and perspectives.
• Expertise in data sources and quality to identify and leverage data across multiple sources, understands data requirements, and evaluates the sufficiency of data for addressing relevant and impactful business questions.
• Expertise in data, business, and customer needs to evaluate and determine ideal analytical and inferential techniques to address business questions.

They will also:

• Share insights and analytical expertise to tell stories of analyses through one or more means.
• Builds, supports, and/or consults others on the execution of formal experiments or prototypes/proofs of concepts, to evaluate the impact of new or changed features or processes.
• Identifies and promotes methods that create efficiency in core work related to analytics and reporting that are reusable, readily discoverable by decision-makers, self-service, and directed to meaningful interpretation of data and driving business decisions.
• Understands the relationship between analytical model(s) and business objectives.
• Maintains expertise in data privacy requirements, responsible and ethical data handling practices, and models compliance with classification and governance rules and regulations.

Some useful skills they may possess:
Algorithm Design and Implementation - The ability to design, analyze, implement, optimize, profile and experimentally evaluate computer algorithms. Includes knowledge of practical applications of algorithms in software engineering.
Analytical Skills - The ability to review quantitative or conceptual problems and situations to draw appropriate and valid conclusions from data presented. This includes analyzing data to determine the most significant elements, identify common elements and themes in situations and actions, and recognize cause and effect relationships.
Automation - Knowledge of automation technologies, methods, and processes used for quality and cost improvements.
Big Data - Knowledge of and ability to use big data, which includes ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. This includes data that is characterized by such a high volume, velocity, and variety to require specific technology and analytical methods for its transformation to value.
Code Review - The ability to apply knowledge about program coding to perform peer reviews of computer source code with the intent to find and fix mistakes, find security loopholes, and correct inefficiencies overlooked in the initial development phase, improving overall code quality.
Compliance Oversight - The ability to comply with the rules, regulations, codes, sanctions and other statutory requirements, guidelines and instructions as defined by governing bodies and organizations that regulate and/or set standards or telecommunications and data security/privacy.
Conflict Resolution - The ability to manage conflict, disharmony, and strife among people and situations, while recognizing and addressing sensitivities.
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.

REQUIRED QUALIFICATIONS

• Bachelor’s Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 4+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis
• OR Master’s Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 2+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis
• OR equivalent experience.
• 2+ years’ experience in visualization and reporting: experience with Power BI for generating dashboards that track metrics, trends, and performance.
• 2+ years’ experience using data for problem solving and to drive process improvements and eliminate inefficiencies.

PREFERRED QUALIFICATIONS

• 2+ years’ experience with cross-functional collaboration: demonstrated experience in collaborating with engineers, manufacturing or build/delivery teams, or other departments to troubleshoot quality issues.
• Proficiency in Programming Languages: Technical proficiency with Python, R, or SQL for data manipulation and analysis, especially with libraries for data science and machine learning (e.g., pandas, NumPy, scikit-learn).
• Previous experience working in or around data centers
• Quality Control or Quality Assurance Background: previous experience in or supporting QC/QA teams, especially in industries like manufacturing, pharmaceuticals, or technology
• Experience with Compliance and Regulatory Standards: Familiarity with standards such as ISO 9001 (Quality Management Systems) or Six Sigma methodologies
• Experience in Monitoring Production Metrics: understanding key performance indicators (KPIs) related to product quality, defect rates, and process efficiency
• Database Management: Proficiency with databases (SQL, NoSQL, or cloud-based data warehouses) is essential for managing large volumes of QC data
• Statistical Analysis for Quality Control: Familiarity with statistical process control (SPC), root cause analysis, or regression analysis to identify trends and deviations in production quality.
• Predictive Analytics: Experience in developing predictive models to anticipate defects or production issues before they occur.
• Root Cause Analysis: Candidates with experience in identifying the root causes of quality issues using data-driven methods (like 5 Whys or Fishbone Diagrams) can significantly impact your QC organization.
• Communication Skills: The ability to communicate technical findings in a non-technical manner is crucial for ensuring that QC data is actionable for management and operations teams.
  Data Analytics IC4 - The typical base pay range for this role across the U.S. is USD $103,800 - $200,300 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,700 - $219,200 per year.
  Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
  Microsoft will accept applications for the role until November 21, 2024.