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Lead Data Engineer

At Northwestern Mutual, we are strong, innovative and growing. We invest in our people. We care and make a positive difference.

Lead Data Engineer (ML Engineer) (P4)

Northwestern Mutual (NM) has been helping people and businesses achieve financial security for over 161 years. Through a distinctive, whole-picture planning approach including both insurance and investments,, we empower people to be financially confident. We combine the expertise of our financial professionals with a personalized digital experience and groundbreaking technology to best serve our clients.

Data is a critical driver of this approach and a cornerstone for how We engage with our customers. To help lead the effort, NM’s Senior Director, Data Engineering & MLOps is seeking a highly motivated, curious, process driven, and passionate Data Engineer to establish a MLOps platform and standard methodologies.

You will be a key member in our newly formed Core Data & Analytics department (CDA). You will collaborate with Data Scientists, Analytical Engineers, Data Scientists, and Product Owners throughout the organization to help unlock the value of data through predictive analytics and operationalized machine learning.

Your responsibilities include but are not limited to:

  • Develop reliable data pipelines that transform and aggregate data from NM’s source systems and data platforms
  • Establish and maintain NM’s data science/ML platforms, with a focus on rapid iteration and operational deployment of predictive models
  • Establish a feature store of curated metrics, attributes, and features for ML models
  • Collaborate closely with data scientists, DevOps Engineers, and enterprise infrastructure teams to enable automation and monitoring across the machine learning lifecycle
  • Develop ML model monitoring pipelines for model performance, data quality.
  • Serve as a team lead of other data engineers, providing support, technical mentorship, and delegating work

You will know you are successful:

  • NM’s MLOps platforms enable the deployment of multiple machine learning models to the production environment
  • Reliable and trusted data pipelines are established, providing critical data for data scientists
  • Ml Models are deployed to production with robust monitoring, capturing key metrics on model performance and data drift
  • You successfully collaborate with your peers to deliver solutions that successfully combine new platforms and older systems
  • Your collaborators are delighted by your delivery focused demeanor, impact to the business, technical excellence

Required Skills:

  • 5+ years in Data Engineering
  • 5+ years public cloud experience (AWS preferred) preferred
  • Expertise in Python preferred
  • Experience with streaming (e.g. Kafka, Kinesis) technologies
  • Experience with data engineering automation and orchestration tools (Airflow, Dagster, Step Functions, etc.)
  • Experience with big data frameworks such as Spark, Beam, AWS Glue, GCP Dataproc/Dataflow
  • Experience with Infrastructure as Code tools such as Terraform and CloudFormation
  • Experience with MLOps platforms (Domino, DataRobot, SageMaker) preferred
  • Experience in Cloud Data Warehouse technology (e.g. Redshift, Snowflake) or equivalent data lake technology (Delta Lake, Iceberg, Hudi)
  • Experience with ELK stack preferred
  • Expertise with Git, code versioning and control, and code deployment standard methodologies
  • Experience and understanding of CI/CD standard methodologies as they relate to data engineering pipelines
  • Ability to collaborate with external groups, understanding their requirements and processes
  • Delivers excellent verbal and written communication to include expression of facts and ideas, interpretation of information and the ability to make clear and convincing presentation
  • Ability to navigate the levels of audiences and articulate ideas to both technical and non-technical audiences
  • Sets and manage priorities efficiently
  • Maintains strong self-motivation and team motivation through high degrees of collaboration

Desired Background:

  • Experience deploying, and operating machine learning pipelines
  • Experience working in a hybrid (on-prem and cloud) infrastructure environment

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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W e are an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender identity or expression, sexual orientation, national origin, disability, age or status as a protected veteran, or any other characteristic protected by law.

If you work or would be working in Colorado or outside of a Corporate location, please click here for information pertaining to compensation and benefits.


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