Sr Analytics Engineer

Northwestern Mutual•Milwaukee, WI

1d•$118,960 - $205,200•Hybrid

About The Position

Our aspiration is to be an insight driven organization where trusted data, enterprise metrics, and analytics inform strategic decision-making. Within the Strategy, Marketing, & Innovation function, the Business Intelligence Center of Excellence seeks to instill and sustain changes that lead to more objective, consistent, and strategically advantageous decision-making through the usage of NM’s valuable data and information. Unlike traditional engineering roles focused primarily on data movement or infrastructure, this role is dedicated to creating reusable analytical assets, defining trusted business logic, implementing enterprise metrics, and establishing governed data structures that power advanced analytics and next-generation AI capabilities. The ideal candidate excels at the intersection of business, data, and analytics, transforming strategic objectives into trusted data products, governed metrics, and scalable analytical solutions that drive enterprise decision-making.

Requirements

Bachelor’s Degree in a related field.
5+ years in analytics, data, or technology-related roles, including 3+ years applying the specified technical skills in platforms such as Databricks, Snowflake, AWS, Atlan, etc.
Demonstrated experience and strong understanding of Large Language Models (LLMs), including prompt engineering, model capabilities, limitations, and practical business applications.
Demonstrated ability to translate ambiguous business concepts into structured metrics, analytical models, and reusable data products.
Ability to work cross-functionally between business and technical stakeholders.
Experience with metric management platforms and strong collaboration skills in researching how metrics are sourced, calculated, and shared.
Strong aptitude for data quality, lineage, provenance, and governance in an analytic-centric environment.
Strong SQL skills and experience with query optimization and performance management.
Successful track record of collecting, designing, and maintaining large data models.
Experience developing large analytical datasets, semantic models, dimensional models, or curated analytical data products.
Strong understanding of modern data modeling principles, including data grain, dimensions, facts, hierarchies, and reusable business logic.
Adaptive Communication - Formulates strategies to be used to convey complex information about services, products, systems, or processes to targeted audiences; communicates and liaises between technical and non-technical audiences.
Business Application - Utilizes both business acumen and technology expertise to translate business requirements/capabilities into technical solutions and applies technical knowledge of a product/platform/application to align it with a particular line of business (LOB) based on the organization's technology needs and business goals.
Cross Functional Partnering & Planning - Facilitates collaboration, communication, coordination, and planning with individuals and teams from different functions within the organization, and who have different areas of expertise, to achieve common goals.
Data Analytics - Creates business knowledge through data analysis and/or uses, maintains, captures, and stores data analysis; applies different types of analysis (e.g., financial, economic, competitive, supplier, industry) and analytical techniques.
Data Integrity - Resolves issues in data to ensure higher accuracy and consistency over its entire lifecycle of design, implementation, and usage.
Data Literacy - Utilizes appropriate data for a particular purpose by thinking critically about information yielded by data analysis; applies data analytics tools/methods and their appropriate purposes and recognizes when data is being misrepresented to resolve issues or escalate to the appropriate party.
Strategic Thinking - Uses critical thinking and knowledge of business demand to plan, design, prioritize and execute high impact initiatives and programs.

Responsibilities

Lead business and technical requirements for development of reusable cross-domain analytical data products with a keen focus on metric certification, lineage identification, and metadata collection.
Partner with business stakeholders to define, document, and align metrics, KPIs, business rules, and analytical requirements to ensure consistency, trust, and enterprise reuse.
Deliver a scalable analytics layer that establishes consistent enterprise metrics (OKRs/KPIs) that enable self-service and build trusted cross-functional business intelligence.
Define analytical data quality rules that align technical standards with business requirements, proactively monitor and manage data drift, and enable trusted analytical outcomes.
Perform routine data validation, reconciliation, and quality assessments across the analytics lifecycle and products supported by BICOE to ensure accurate, reliable, and trusted outcomes.
Be a driver in cataloging cross-domain analytical products ensuring enterprise visibility and understanding of how to use the asset in Atlan.
Be a zealot for adoption and reuse of analytical data products and other enterprise approved assets.
Apply vigorous curiosity for emerging technologies that improve data discoverability, contextual understanding, trusted analytical consumption, and AI-enabled decision support.
Partner with Data Solutions & Enablement and business stakeholders to ensure end-to-end alignment with enterprise data standards, governance practices, and approved data sources.
Responsible for establishing mentorship and coaching community within and beyond the BICOE.