Data Engineer

Northwestern Mutual; Milwaukee (WI); Hybrid; USD 98,000 - 160,000; Full time

Benefits offered by this job

Telecommuting 2 days/week

Job summary

Northwestern Mutual Life Insurance Company in Milwaukee, WI seeks a Data Engineer to design and build scalable data pipelines and data models using Big Data technologies. You will ingest, transform, and load data from multiple sources, architect data infrastructure for analytics, and develop dashboards for leadership.

The role requires Python, SQL, Apache Spark (PySpark), and strong data modeling skills, with Agile/DevOps experience.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Information Technology, Data Science, or a related field.
• At least 2 years of experience developing data pipelines, ETL/ELT workflows, and data processing using Python and SQL.
• Experience with Big Data technologies including JVM, Apache Spark, PySpark for large-scale processing.
• Designing data models, schemas, and storage architectures for analytical and operational use.
• Familiarity with Agile/Scrum and DevOps practices in a collaborative team.
• Experience with data integration patterns and tooling (ELT/ETL, replication, event streaming).
• Awareness of software quality standards and best practices.

Responsibilities

• Design and build scalable data pipelines and data models using Big Data tech.
• Ingest, transform, and load structured and unstructured data from multiple sources.
• Develop analytical datasets, KPIs, and dashboards for stakeholders and leadership.
• Create ML-ready data features and pipelines for model training and deployment.
• Monitor data quality, lineage, and model performance in production.

Skills

Data pipelines

ETL/ELT

Python

SQL

Spark

PySpark

JVM

Education

Bachelor’s degree in Computer Science or related field

Tools

Apache Spark

PySpark

SQL

Python

JVM (Java/Scala)

Job description

Job Description

Job Description: The Data Engineer at Northwestern Mutual Life Insurance Company in Milwaukee, WI will design and build scalable data pipelines and data models using Big Data technologies. Ingest, transform, and load structured and unstructured data from multiple source systems. Architect data infrastructure across the Financial Planning and Illustrations domains to power analytics, reporting, KPI tracking, predictive modeling, and machine learning workflows. Build analytical datasets, KPI metrics, and interactive dashboards using SQL, Python, and visualization tools. Create trend analyses, performance reports, and business intelligence solutions for Financial Representatives, business stakeholders, and leadership. Develop data aggregation and reporting frameworks that translate raw financial planning data into actionable insights for decision-making. Design and build predictive models and machine learning (ML) solutions for client retention analysis, churn forecasting, and financial planning optimization. Develop feature engineering pipelines and curated training datasets. Deploy ML models into production environments and monitor model performance, accuracy, and drift. Architect and develop AI-powered solutions to automate data pipeline monitoring, data quality detection, and data integration issue resolution. Build intelligent anomaly detection systems that proactively identify data inconsistencies, schema drift, and pipeline failures before they impact downstream analytics and business reporting. Build and deploy end-to-end data products, ETL/ELT jobs, and data processing workflows using SQL, Python, and Big Data tools. Design data storage solutions, schema architectures, and optimized query structures within the enterprise data platform. Implement continuous deployment and integration practices across all data engineering solutions. Design and implement data quality frameworks, automated validation rules, and reconciliation processes. Build data auditing systems to detect root causes of data issues across the enterprise data ecosystem. Develop data governance, cataloging, and metadata management standards across all data assets, with emphasis on PII compliance, access controls, and regulatory adherence. Build monitoring and alerting systems for production data pipelines and analytics solutions. Develop automated health checks and performance optimization routines. Mentor junior developers and conduct code reviews to uphold engineering standards and code quality. Lead cross-functional collaboration with platform, MLOps, and data management teams to architect scalable, production-grade data and AI solutions. Drive Agile delivery through sprint planning, backlog grooming, story writing, sizing, and demo sessions. Telecommuting permitted 2 days per week. Salary $97,552- $159,770 per year.

Minimum Requirements

Minimum Requirements: Bachelor’s degree in Computer Science, Computer Engineering, Information Technology, Data Science, or a related field and 2 years of experience as data engineer or related occupation. Experience must include 2 years of experience with each of the following: (1) developing data pipelines, ETL/ELT workflows, and data processing solutions using Python and SQL; (2) Big Data technologies including JVM (Java, Scala), Apache Spark, PySpark for large-scale data processing and analytics; (3) designing and implementing data models, database schemas, and data storage architectures for analytical and operational use; (4) Agile/Scrum software development methodologies and DevOps practices in a collaborative team environment; (5) Data Integration Patterns and Tooling including ELT/ETL, Replication, Event Streaming, and Virtualization to support batch and real-time data needs; and (6) applying Software and Quality Standards in a professional development environment.

Fairness and Transparency

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. If noted, this is standard pay structure for this position.

Career Development

Grow your career with a best-in-class company that puts our clients' interests at the center of all we do. Northwestern Mutual is an equal opportunity employer that welcomes talented individuals of all backgrounds.

Culture Commitment

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.

Company Values

At Northwestern Mutual, we believe relationships are built on trust. That our lives and our work matter. These beliefs launched our company over 160 years ago. Today, they're just a few of the reasons why people choose to build careers at Northwestern Mutual.

Growth and Locations

What started in Milwaukee, WI has grown into 7,000+ home office professionals split across 3 campuses: New York City, Franklin and downtown Milwaukee (HQ) - each one bringing with it its own unique talent and culture. In a company with such a long and storied history, this may be the most exciting and important time to be a part of Northwestern Mutual as we are growing our digital and tech capabilities and are always on the lookout for bright, tech-savvy candidates.

Equal Opportunity Statement

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.