Start-Up Vibes with The Stability of a Fortune 100 Company.
The Role
Lead the design and delivery of data platforms and pipelines, ensuring data quality and governance, while mentoring engineering teams and optimizing costs.
Summary Generated by Built In
About the team
Field domain data team build and manage data pipelines, create pipelines to collect data from multiple sources (databases, APIs, files), transform, and move data into storage systems (Data Mesh/data lakes / warehouses), Automate ETL (Extract, Transform, Load) workflows. Design scalable data architecture, systems that can handle large-scale data reliably and efficiently. Ensure data quality, governance & security, validate and clean incoming data, apply governance policies (who can access what), maintain compliance and security controls.We work with other teams across organization, collaborate with Product/ business teams (to understand data needs), Data scientists (to support ML/AI use cases), DevOps / platform teams.
What You'll do- Lead the design and delivery of end-to-end data platforms and pipelines (batch and streaming) using AWS services to support analytics, reporting, ML, and operational use cases.- Define and own data architecture decisions, standards, and best practices. Produce and maintain Architecture Decision Records (ADRs), runbooks, and high-quality diagrams.- Architect and implement data lake and/or data warehouse solutions (ingestion, storage, transformation, serving) using S3, Glue, Redshift, Athena, and related services.- Build and optimize ETL/ELT workflows with Spark, Glue, Lambda, Step Functions, and orchestration frameworks (Airflow, Dagster).- Design and operate streaming ingestion and processing using Kinesis, MSK, and Kafka ecosystems; collaborate on re-architecture efforts to reduce cost and improve resilience.- Drive data modeling, schema design, partitioning, and query optimization for large data sets to meet performance and cost targets.- Establish and operationalize data quality, validation, observability, lineage, and metadata practices (Glue Data Catalog, Data Hub/Amundsen or equivalent).- Implement robust security, governance, and compliance controls (IAM, Lake Formation, KMS, VPC, data masking/security scanning) and collaborate with security and privacy teams.- Champion cost optimization across the data stack (serverless architectures, right-sizing, Graviton/spot/commitment strategies) and provide continuous cost governance.- Own production reliability: monitoring, SLIs/SLOs, incident response, postmortems, and continuous improvements.- Lead and mentor engineers, run design reviews, and promote cross-team collaboration with product, analytics, ML, and platform teams.- Influence roadmap, capacity planning, and hiring for the data engineering function; represent the team in senior technical forums.What You'll bring to the role- 7+ years of hands-on experience in data engineering, architecting and operating data platforms at scale.- Demonstrated leadership on large, complex data projects and strong ability to influence technical and product stakeholders.- Extensive hands-on experience with AWS data services: S3, Glue, Redshift (Spectrum/RA3), Athena, EMR, Lambda, Kinesis/MSK, DMS.- Strong programming skills in Python and/or Scala (or Java); proven track record writing production-quality, testable code.- Deep expertise in SQL with experience designing and optimizing queries for high-volume data.- Experience with distributed processing frameworks (Spark) and modern ETL/ELT patterns.- Proficiency with orchestration and workflow tools (Airflow, Step Functions, Dagster) and CI/CD for data pipelines.- Strong skills in infrastructure-as-code (Terraform, CloudFormation, or CDK) and GitOps practices.- Experience implementing data security, governance, and access controls at scale.- Expertise in observability, monitoring, and incident management (CloudWatch, Prometheus, Grafana, structured logging, tracing).- Excellent communication skills and proven ability to mentor and lead engineers.Preferred Qualifications- AWS certifications (e.g., AWS Certified Data Analytics - Specialty, AWS Certified Solutions Architect) or equivalent.- Experience with data lakehouse technologies (Delta Lake, Iceberg, Databricks Unity Catalog), and large-scale performance troubleshooting.- Familiarity with metadata and lineage tooling (Amundsen, DataHub, OpenLineage).- Prior experience with cost-optimization programs (Graviton, serverless, spot instances) and demonstrable results.- Contributions to open-source projects, publications, or conference presentations on data engineering topics.- Experience working in regulated industries (finance, healthcare) and implementing compliance controls.
-AI usage for building Data Pipelines.Skills You'll have- Strategic thinker with strong problem-solving and architectural judgment.- Ability to manage multiple complex priorities and deliver high-quality work under deadlines.- Strong mentoring and team leadership skills; fosters a culture of knowledge sharing and continuous improvement.- Customer-focused: translates business needs into pragmatic, maintainable technical solutions.- Strong attention to detail, excellent documentation habits, and commitment to operational excellence.
Compensation Range:
Pay Range - Start:
$118,960.00
Pay Range - End:
$178,440.00
Geographic Specific Pay Structure:
Structure 110:
$130,880.00 USD - $196,320.00 USD
Structure 115:
$136,800.00 USD - $205,200.00 USD
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.
Skills
Analytical Thinking (NM) - Advanced, Customer Centricity (NM) - Advanced, Strategic Thinking (NM) - Advanced, Application Security (NM) - Advanced, Talent Development & Planning (NM) - Beginner, Root Cause Analysis & Decision Quality (NM) - Advanced, Release Management (NM) - Advanced, Cross Functional Partnering & Planning (NM) - Intermediate, Cloud Technology (NM) - Intermediate, DevOps (NM) - Advanced, Accountability (NM) - Beginner, Software Problem Solving (NM) - Advanced, Business Application (NM) - Intermediate, Technical Problem Solving (NM) - Advanced, Coaching & Mentoring (NM) - Intermediate, IT Strategy (NM) - Intermediate, Adaptive Communication (NM) - Advanced, Software Development (NM) - Advanced, Data Literacy (NM) - Advanced, Learning Agility & Critical Thinking (NM) - Advanced, Application Performance Management (NM) - Intermediate
FIND YOUR FUTURE
We're excited about the potential people bring to Northwestern Mutual. You can grow your career here while enjoying first-class perks, benefits, and our commitment to a culture of belonging.
Field domain data team build and manage data pipelines, create pipelines to collect data from multiple sources (databases, APIs, files), transform, and move data into storage systems (Data Mesh/data lakes / warehouses), Automate ETL (Extract, Transform, Load) workflows. Design scalable data architecture, systems that can handle large-scale data reliably and efficiently. Ensure data quality, governance & security, validate and clean incoming data, apply governance policies (who can access what), maintain compliance and security controls.We work with other teams across organization, collaborate with Product/ business teams (to understand data needs), Data scientists (to support ML/AI use cases), DevOps / platform teams.
What You'll do- Lead the design and delivery of end-to-end data platforms and pipelines (batch and streaming) using AWS services to support analytics, reporting, ML, and operational use cases.- Define and own data architecture decisions, standards, and best practices. Produce and maintain Architecture Decision Records (ADRs), runbooks, and high-quality diagrams.- Architect and implement data lake and/or data warehouse solutions (ingestion, storage, transformation, serving) using S3, Glue, Redshift, Athena, and related services.- Build and optimize ETL/ELT workflows with Spark, Glue, Lambda, Step Functions, and orchestration frameworks (Airflow, Dagster).- Design and operate streaming ingestion and processing using Kinesis, MSK, and Kafka ecosystems; collaborate on re-architecture efforts to reduce cost and improve resilience.- Drive data modeling, schema design, partitioning, and query optimization for large data sets to meet performance and cost targets.- Establish and operationalize data quality, validation, observability, lineage, and metadata practices (Glue Data Catalog, Data Hub/Amundsen or equivalent).- Implement robust security, governance, and compliance controls (IAM, Lake Formation, KMS, VPC, data masking/security scanning) and collaborate with security and privacy teams.- Champion cost optimization across the data stack (serverless architectures, right-sizing, Graviton/spot/commitment strategies) and provide continuous cost governance.- Own production reliability: monitoring, SLIs/SLOs, incident response, postmortems, and continuous improvements.- Lead and mentor engineers, run design reviews, and promote cross-team collaboration with product, analytics, ML, and platform teams.- Influence roadmap, capacity planning, and hiring for the data engineering function; represent the team in senior technical forums.What You'll bring to the role- 7+ years of hands-on experience in data engineering, architecting and operating data platforms at scale.- Demonstrated leadership on large, complex data projects and strong ability to influence technical and product stakeholders.- Extensive hands-on experience with AWS data services: S3, Glue, Redshift (Spectrum/RA3), Athena, EMR, Lambda, Kinesis/MSK, DMS.- Strong programming skills in Python and/or Scala (or Java); proven track record writing production-quality, testable code.- Deep expertise in SQL with experience designing and optimizing queries for high-volume data.- Experience with distributed processing frameworks (Spark) and modern ETL/ELT patterns.- Proficiency with orchestration and workflow tools (Airflow, Step Functions, Dagster) and CI/CD for data pipelines.- Strong skills in infrastructure-as-code (Terraform, CloudFormation, or CDK) and GitOps practices.- Experience implementing data security, governance, and access controls at scale.- Expertise in observability, monitoring, and incident management (CloudWatch, Prometheus, Grafana, structured logging, tracing).- Excellent communication skills and proven ability to mentor and lead engineers.Preferred Qualifications- AWS certifications (e.g., AWS Certified Data Analytics - Specialty, AWS Certified Solutions Architect) or equivalent.- Experience with data lakehouse technologies (Delta Lake, Iceberg, Databricks Unity Catalog), and large-scale performance troubleshooting.- Familiarity with metadata and lineage tooling (Amundsen, DataHub, OpenLineage).- Prior experience with cost-optimization programs (Graviton, serverless, spot instances) and demonstrable results.- Contributions to open-source projects, publications, or conference presentations on data engineering topics.- Experience working in regulated industries (finance, healthcare) and implementing compliance controls.
-AI usage for building Data Pipelines.Skills You'll have- Strategic thinker with strong problem-solving and architectural judgment.- Ability to manage multiple complex priorities and deliver high-quality work under deadlines.- Strong mentoring and team leadership skills; fosters a culture of knowledge sharing and continuous improvement.- Customer-focused: translates business needs into pragmatic, maintainable technical solutions.- Strong attention to detail, excellent documentation habits, and commitment to operational excellence.
Compensation Range:
Pay Range - Start:
$118,960.00
Pay Range - End:
$178,440.00
Geographic Specific Pay Structure:
Structure 110:
$130,880.00 USD - $196,320.00 USD
Structure 115:
$136,800.00 USD - $205,200.00 USD
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.
Skills
Analytical Thinking (NM) - Advanced, Customer Centricity (NM) - Advanced, Strategic Thinking (NM) - Advanced, Application Security (NM) - Advanced, Talent Development & Planning (NM) - Beginner, Root Cause Analysis & Decision Quality (NM) - Advanced, Release Management (NM) - Advanced, Cross Functional Partnering & Planning (NM) - Intermediate, Cloud Technology (NM) - Intermediate, DevOps (NM) - Advanced, Accountability (NM) - Beginner, Software Problem Solving (NM) - Advanced, Business Application (NM) - Intermediate, Technical Problem Solving (NM) - Advanced, Coaching & Mentoring (NM) - Intermediate, IT Strategy (NM) - Intermediate, Adaptive Communication (NM) - Advanced, Software Development (NM) - Advanced, Data Literacy (NM) - Advanced, Learning Agility & Critical Thinking (NM) - Advanced, Application Performance Management (NM) - Intermediate
FIND YOUR FUTURE
We're excited about the potential people bring to Northwestern Mutual. You can grow your career here while enjoying first-class perks, benefits, and our commitment to a culture of belonging.
- Flexible work schedules
- Concierge service
- Comprehensive benefits
- Employee resource groups
Skills Required
- 7+ years of hands-on experience in data engineering
- Extensive hands-on experience with AWS data services
- Strong programming skills in Python and/or Scala
- Deep expertise in SQL with experience designing and optimizing queries
- Experience with distributed processing frameworks (Spark)
- Proficiency with orchestration and workflow tools (Airflow, Step Functions, Dagster)
- Strong skills in infrastructure-as-code (Terraform, CloudFormation, or CDK)
- Experience implementing data security, governance, and access controls
- Excellent communication skills and proven ability to mentor and lead engineers
What the Team is Saying
Chris
Regional Financial Consultant
Chester
Senior Cybersecurity Engineer
Northwestern Mutual Compensation & Benefits Highlights
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Retirement Support — The package includes both a 401(k) and a company‑funded cash balance pension with automatic company contributions and disclosed vesting. This dual‑plan structure and cash‑balance credits strengthen long‑term savings support.
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Parental & Family Support — Paid parental leave, caregiving leave, and adoption/surrogacy assistance are explicitly provided for eligible employees. Fertility and family‑building resources are also highlighted as part of the offering.
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Healthcare Strength — Medical, dental, and vision coverage are paired with mental‑health resources and access to on‑site health centers in key locations. Fitness centers and reimbursements extend health and wellness support beyond core insurance.
Northwestern Mutual Insights
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The Company
What We Do
You’ll Like It Here At Northwestern Mutual, we believe that our lives and our work matter. And that doing what’s right is good for everyone. We follow through by designing tech that improves the community and cultivating creative ways to make finance accessible anywhere. These guiding principles have allowed our company to grow for more than 160 years. Here, you’ll be with a team who emphasizes integrity and prioritizes security to design experiences that better everyone. You’ll work in cross functional teams to create optimal solutions that are rooted in innovative strategy and thoughtful execution. And you’re provided development tools and opportunities to become a leader all with the support of a collaborative team. You’ll be surrounded in a culture that values innovation and works to always evolve to stay ahead of trends and client needs. We are intentional in seeking out team members who will challenge us. Our employees choose us for the career opportunities, commitment to philanthropy and desire to have a meaningful impact in the lives of our clients. You have career passions and goals. We have ambition and opportunity for you to grow your future in tech. Discover today: https://careers.northwesternmutual.com/
Why Work With Us
We invest in our people. We know careers are about choices, so we provide intentional opportunity. Here you can build creative ways to make finance accessible anywhere and revolutionize traditional processes. As a mutual company, our focus is our people — whether professional development or investments in the community.
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Northwestern Mutual Teams
Northwestern Mutual Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We offer a flexible, hybrid approach for our employees . Teams are in the office a few days a week and work from home the others.
Typical time on-site:
Flexible
