200+ applicants

Company

Original Job Post

Northwestern Mutual · 6 days ago

Analytics Engineer

Milwaukee, WI

Full-time

Hybrid

Entry Level

$75K/yr - $140K/yr

1+ years exp

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Responsibilities

Partner with Data Scientists, Analysts, and business partners to develop AI solutions using Databricks, AWS Cloud, and microservice architecture.

Acquire, analyze, and structure data for analytical consumption, consulting with data consumers to identify relevant datasets.

Develop data products with continuous deployment practices and apply engineering best practices for data analytics products.

Participate in agile story authoring, code reviews, and provide feedback to the team.

Collaborate in developing and deploying microservices and AWS serverless apps, ensuring data accuracy and quality.

Utilize SQL, Python, R, Gitlab CI/CD, and modern data platforms like Databricks, Snowflake, and AWS Sagemaker for data processing and model training.

Build distributed data pipelines using Apache Spark, and ensure compliance with regulations on data privacy.

Communicate technical solutions effectively to both technical and non-technical teams, demonstrating strong analytical and problem-solving skills.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

SQLPythonRGitlab CI/CDDatabase modelsDBMSDatabricksSnowflakeAWS SagemakerData accuracyMicroservicesKubernetesAWS LambdaS3SQSStep FunctionsETLApache SparkData sciencePII data regulationsTechnical solution explanationAgile methodologiesDevOpsProblem-solvingAnalyticalCommunicationSelf-motivatedPowerBITableau

Required

Bachelor's Degree

1-3 years of professional experience

At least 1 year of professional experience in data acquisition, cleansing, feature engineering, debugging and software documentation, using languages such as SQL, Python, or R

Experience using continuous integration and deployment concepts via Gitlab CI/CD

Experience navigating various types of database models and DBMS’s to create data sets for analytics and model training and development

Understanding of modern data platforms such as Databricks, Snowflake, or AWS Sagemaker

Experience with testing or data accuracy/quality designs

Experience in building and deploying microservices via Kubernetes

Experience in building and deploying AWS serverless apps using Lambda, S3, SQS, Step Functions, etc

Strong SQL skills and background in ETL

Familiar with developing distributed data pipelines using Apache Spark

Understanding of analytics and data science applications

Familiar and aware of regulations around the use of PII data

Ability to explain their technical solutions to technical teams and non-technical teams

Excellent written and verbal communication skills