Responsible for supporting the onboarding, ingestion, and transformation of structured and unstructured data into AWS cloud environments; work within the Product team to enable regulatory and statistical models across domains including Mortgage, Credit Card, and Auto; collaborate with Data Scientists, Architects, and cross-functional stakeholders to design, develop, and implement scalable data engineering workflows and transformation logic to ensure efficient data processing, validation, and delivery; assist in onboarding datasets from multiple sources into AWS by performing data analysis, profiling, and validation; perform data ingestion from various sources including databases and APIs; conduct data profiling and exploratory data analysis to identify trends, anomalies, and data quality issues; develop, optimize, and maintain data pipelines using Python and SQL to ensure scalability and performance; monitor data pipelines and workflows, troubleshoot failures, perform root cause analysis, and implement fixes to ensure data reliability and availability; contribute to migration efforts and data transformation initiatives across platforms such as AWS, Snowflake, and Databricks; support CI/CD processes including version control, deployment, and testing using Git and Agile methodologies; apply relational data modeling concepts including Star Schema, normalization, and key design, as well as AWS, Python, R, Pandas, PostgreSQL, Teradata, Snowflake, and data modeling tools to complete assigned tasks; interpret, review, and validate code; perform code reviews and resolve defects and performance issues; develop and support lightweight APIs and internal tools using Python-based frameworks including FastAPI and Swagger UI, to enable data access and workflow automation; automate data processing tasks using Python and SQL; utilize AI-assisted development tools including GitHub Copilot to enhance development efficiency; utilize and apply knowledge of Python, SQL, cloud platforms, data visualization, data warehousing, version control, relational data modeling, machine learning modeling, data ingestion, statistical data analysis/profiling, APIs, and Agile development methodologies to complete assigned tasks; leverage advanced analytics and emerging technologies, including machine learning techniques and large language models (LLMs), to support data modeling and automation initiatives; support data governance efforts including data quality, metadata management, and compliance; collaborate with stakeholders to translate business requirements into data-driven solutions; and document processes and workflows for maintainability and knowledge sharing.

Location:

Troy, Michigan and multiple undetermined worksites throughout the US;

Salary:

$145,600 per year (Benefits include medical, dental, vision, 401(k), STD/LTD, life insurance, and EAP)

Education:

Bachelors - Data Science, Business Analytics, Data Engineering, or in a related field of study (will accept equivalent foreign degree).

Training:

None Experience:

Five (5) years in the position above, as a Senior data Analyst, as a Trainee Decision Scientist, as an Associate Manager - Digital and Advanced Analytics, as a Lead Data Engineer, or in a related occupation. Populus Group is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law. If you would like to request a reasonable accommodation, such as the modification or adjustment of the job application process or interviewing process due to a disability, please email HR@PopulusGroup.com for other accommodation options.