What you will do:

The People Analytics Data Engineer will play a crucial role in managing and enhancing our data infrastructure and analytics capabilities. This individual will lead the cloud migration of the current systems from on-premises to AWS utilizing RDS Aurora Postgres, AWS Glue, and other AWS services. Key responsibilities include collaborating with internal teams to provide analytics-ready datasets, maintaining AWS infrastructure, and implementing best practices for performance and version control. The role demands a strong background in relational databases, data warehousing, and experience with Python and SQL, as well as a deep understanding of AWS services and DevOps practices. Previous experience in transitioning systems from on-premises to the cloud is required.

How you will do it:

• Manage the People Analytics cloud migration from on-prem SSIS jobs to Python/Spark shell jobs within AWS Glue.

• Own and maintain complex ETL pipelines adhering to business rules and upstream changes.

• Responsible for implementing best practices around system integration, security, performance, version control, and data management within the People Analytics team.

• Collaborate with internal clients (such as Data Scientists and HR Business Partners) to provision analytics-ready datasets.

• Provision and maintain AWS Infrastructure using Gitlab and Terraform.

• Continually monitor data pipelines to ensure stability, reliability, and quality of the data.

• Work with reporting partners to maintain up-to-date field definitions within the data warehouse.

Bring your best! What this role needs:

• 6-8 years of professional experience.

• Strong skills in relational databases and data warehousing.

• Ability to utilize Python and SQL for data extraction and processing.

• Experience with DevOps practices and building cloud infrastructure using Infrastructure as Code.

• Experience with data modeling and implementing slow-changing dimensions.

• Prior experience with AWS (Preferably AWS RDS, Glue, Lambda, and S3).

• Advanced knowledge of SQL and Python (preferably Pandas and PySpark) is preferred.

• Proven experience in designing, building, and maintaining scalable data pipelines within AWS preferred.

• Working knowledge of AWS services: AWS Glue, Security groups, IAM Roles, Aurora Postgres, Lambda Functions and S3 buckets preferred.

• Ability to automate deployment and management of AWS data infrastructure using Terraform preferred.

• Experience extracting and normalizing JSON and XML endpoints preferred.

• Experience implementing DAGs to orchestrate ETL jobs preferred.

• Ability to utilize Splunk when diagnosing and resolving firewall issues preferred.

• Experience managing CI/CD pipelines within GitLab preferred.

• Prior experience with SSIS and SQL Server preferred.

• Prior experience working within source systems (such as Workday) to prepare raw reports ready for extraction preferred.

#LI-Hybrid

$110,040.00

$204,360.00

Northwestern Mutual pays on a geographic-specific salary structure and placement in the salary range for this position will be determined by a number of factors including the skills, education, training, credentials and experience of the candidate; the scope, complexity as well as the cost of labor in the market; and other conditions of employment. At Northwestern Mutual, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. Please note that the salary range listed in the posting is the standard pay structure. Positions in certain locations (such as California) may provide an increase on the standard pay structure based on the location. Please click here for additional information relating to location-based pay structures.

We 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 California, Colorado, New York City, Washington or outside of a Corporate location, please click here for information pertaining to compensation and benefits.