Senior Software Engineer

Northwestern Mutual offers flexible work schedules, concierge service, comprehensive benefits, and employee resource groups. This onsite Senior Software Engineer role in Milwaukee, WI provides a competitive salary ranging from USD 118,960 to 205,200 per year and focuses on designing and delivering end-to-end data platforms and pipelines on AWS to support analytics, reporting, ML, and operations. You will own data architecture, governance, security, cost optimization, and production reliability while mentoring engineers.

Benefits

• Flexible work schedules
• Concierge service
• Comprehensive benefits
• Employee resource groups

Responsibilities

• Lead design and delivery of end-to-end data platforms and pipelines (batch and streaming) on AWS to support analytics, reporting, ML, and operations.
• 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 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.

Requirements

• 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.

Technologies

• S3
• Glue
• Redshift
• Athena
• EMR
• Lambda
• Kinesis
• MSK
• DMS
• IAM
• Lake Formation
• KMS
• VPC
• Glue Data Catalog
• Data Hub
• Amundsen
• OpenLineage
• Delta Lake
• Iceberg
• Databricks Unity Catalog
• Kafka
• Spark
• Airflow
• Dagster
• Step Functions
• Terraform
• CloudFormation
• CDK
• GitOps
• Python
• Scala
• Java
• SQL
• CloudWatch
• Prometheus
• Grafana