Senior Engineer

TruStage•Madison, WI

1d•$111,800 - $167,700•Hybrid

About The Position

At TruStage, we’re on a mission to make a brighter financial future accessible to everyone. We put people first, and work hand in hand with employees and customers to create a diverse and inclusive environment. Passionate about building insurance and financial services solutions, we push the boundaries of what’s possible. We need you to help us shape what’s next. You’ll be encouraged to share your experiences, ideas and skills to help others take control of their financial future. Join a team that has received numerous awards for being a top place to work: TruStage awards and recognition

Requirements

Bachelor’s degree in computer science, economics, statistics, information management, engineering, or related field, or equivalent combination of education and/or related professional work experience.
6+ years of experience in analytics engineering, data engineering, or related field.
Strong proficiency in SQL, Python, and R; extensive experience with Snowflake, Alteryx, Azure, Git and business intelligence tools.
Advanced understanding of database design, data modeling, and data quality assurance.
Strong analytical and problem-solving skills.
Excellent communication, documentation, organizational, and project management skills.
Ability to manage small project teams and provide mentorship to junior members.

Responsibilities

Lead the design and optimization of complex ETL/ELT pipelines using tools such as Alteryx, Azure Data Factory, or similar.
Ensure data ingestion processes into data warehousing solutions like Snowflake are accurate, reliable, and consistent.
Mentor junior engineers in best practices for data pipeline development.
Lead the creation and maintenance of advanced dimensional data models in data warehousing solutions.
Integrate multiple complex data sources to provide actionable insights and support analytical queries, processes, Data Science needs, and improve reporting performance.
Implement advanced data transformations and aggregation techniques.
Develop comprehensive data quality frameworks and automated validation processes.
Implement advanced techniques for anomaly detection and correction.
Ensure consistent high data integrity standards across platforms.
Lead cross-functional collaboration to gather requirements and translate business objectives into technical solutions.
Facilitate knowledge sharing on best practices for tools and data.
Foster effective communication between teams.
Ensure comprehensive documentation of data pipelines, data models, and technical specifications.
Maintain detailed documentation for complex data processes.
Support data governance requirements through accurate data lineage and metadata documentation.
Lead ongoing support for data pipelines, data models, and analytical systems.
Develop proactive monitoring solutions to identify and resolve data processing issues.
Ensure system reliability and performance.
Lead optimization efforts for complex data architectures.
Implement advanced techniques for data management and optimization, including indexing, partitioning, and query optimization.
Continuously evaluate and improve data processes and architectures.
Lead compliance efforts, ensuring adherence to established Data Governance best practices.
Mentor junior staff on best practices for data compliance.
Ensure data usage meets regulatory and audit requirements.
Develop leadership skills and manage small to mid-size team projects.
Mentor junior team members and foster a collaborative environment.