Job description

What You ll Do: Lead day-to-day work to acquire, analyze, combine, synthesize, and structure data with clear definitions and sources for analytical consumption Consult with data consumers to identify meaningful datasets for analytical consumption Lead day-to-day development of data products using continuous deployment and integration practices Apply engineering best practices in order to analyze, design, develop, deploy and support data analytics products Participate in agile story authoring, sizing, and demo sessions for product features Lead code reviews and provide feedback to the team Mentor junior engineers What You ll Bring to the Role: Bachelor s Degree Experience designing and developing solutions using Microsoft Power Platform technologies, including Power Apps, Power Automate, Power BI, Dataverse, and related services. At least 4 years of professional experience in data acquisition, cleansing, feature engineering, debugging and software documentation, using modern languages and practices Experience using continuous integration and deployment concepts At least 3 year experience with specific technical requirements/platforms will vary (i.e. AWS data science and analytics cloud technologies such as S3, EMR, Spark, PySpark, RDS, JupyterLab, Sagemaker, etc., data warehouses suchas Redshift or Snowflake; and digital analytics tools such as Adobe Analytics and Heap) Proficiency navigating various types of database models and DBMS’s to create data sets for analytics and model training and development Experience developing solutions using agile methods Experience working in data lake environments Experience guiding the work of junior developers Experience with Testing or data accuracy/quality designs Advanced programming skills Strong Python and cloud compute skills Strong SQL skills and background in ETL Deep understanding of distributed data systems and applications. Proficiency with data lake design and implementation considerations such as columnar storage formats (Parquet) and partitioning Deep understanding of analytics and data science applications Deep understanding of machine learning systems Development of requirement driven data models such dimensional and relational. Deep understanding of the business domain and the meaning of the data in it to accurately identify key and associated data which can be extracted, transformed and loaded for effective consumption downstream. Develop the data flow so that data can be shared across the company with one source of truth being the goal. Understanding and awareness of regulations around the use of PII data. See the big picture and able to incorporate business understanding into design and approach to achieve current value and prepare for future benefit. Ability to provide thought leadership throughout the local scrum team Ability to explain technical solutions to technical teams and non-technical teams Exceptional analytical, conceptual, and problem-solving skills. Excellent written and verbal communication skills Self-motivated and able to work with minimal direction Preferred: Experience with Agile methodologies, experience in DevOps environment, Experience with user adhoc tools: power bi, business objects, Tableau; Consulting experience Skills You Have: Analytical Thinking: Creates business knowledge through data analysis and applies appropriate analytical methods to inform decisions. Data Analytics : Core advanced capability for turning data into actionable business knowledge. Engineering Expertise & Practices: Explores engineering judgment, maintainability, quality, and technical practices. Adaptive Communication: Conveys complex information about products, systems, or processes to targeted technical and non-technical audiences. Compensation Range: Pay Range - Start: $118,960.00 Pay Range - End: $178,440.00 Geographic Specific Pay Structure: Structure 110: Structure 115: We believe in fairness and transparency. It’s why we share the salary range for most of our roles. However, final salaries are based on a number of factors, including the skills and experience of the candidate; the current market; location of the candidate; and other factors uncovered in the hiring process. The standard pay structure is listed but if you’re living in California, New York City or other eligible location, geographic specific pay structures, compensation and benefits could be applicable, click here to learn more. Grow your career with a best-in-class company that puts our clients interests at the center of all we do. Get started now! Northwestern Mutual is an equal opportunity employer that welcomes talented individuals of all backgrounds. We are committed to creating and maintaining an environment in which each employee can contribute creative ideas, seek challenges, assume leadership and continue to focus on meeting and exceeding business and personal objectives.

Requirements

Must-haves

Lead day-to-day work to acquire, analyze, combine, synthesize, and structure data with clear definitions and sources for analytical consumption
Consult with data consumers to identify meaningful datasets for analytical consumption
Lead day-to-day development of data products using continuous deployment and integration practices
Apply engineering best practices in order to analyze, design, develop, deploy and support data analytics products
Participate in agile story authoring, sizing, and demo sessions for product features
Lead code reviews and provide feedback to the team
Mentor junior engineers
Bachelor s Degree
Experience designing and developing solutions using Microsoft Power Platform technologies, including Power Apps, Power Automate, Power BI, Dataverse, and related services.
At least 4 years of professional experience in data acquisition, cleansing, feature engineering, debugging and software documentation, using modern languages and practices
Experience using continuous integration and deployment concepts
Proficiency navigating various types of database models and DBMS’s to create data sets for analytics and model training and development
Experience developing solutions using agile methods
Experience working in data lake environments
Experience guiding the work of junior developers
Experience with Testing or data accuracy/quality designs
Advanced programming skills
Strong Python and cloud compute skills
Strong SQL skills and background in ETL
Deep understanding of distributed data systems and applications.
Proficiency with data lake design and implementation considerations such as columnar storage formats (Parquet) and partitioning
Deep understanding of analytics and data science applications
Deep understanding of machine learning systems

Nice-to-haves

Preferred: Experience with Agile methodologies, experience in DevOps environment, Experience with user adhoc tools: power bi, business objects, Tableau; Consulting experience

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

agileawspythonsqlmachine learningscrum

Platform: workday
Effort: long