Senior Data Analytics Engineer

Analytics Engineer

Propelus® simplifies workforce compliance management across healthcare. Our innovative technology and strategic partnerships empower millions of professionals, their employers, and regulators to work together, creating a connected and efficient healthcare ecosystem.

As a trusted leader for over 20 years, Propelus has focused on bringing more good into the lives of the people and organizations serving healthcare. We deliver seamless compliance solutions to millions. We leverage market-leading technology and essential data to simplify complex operations, reduce risk, and champion a safer, healthier, and happier workforce.

Job Summary: As an Analytics Engineer, you will play a crucial role in transforming raw data into actionable insights to support data-driven decision-making across the company. You will work independently on assigned projects, collaborating with data scientists, product managers, and engineers to build, maintain, and improve our data infrastructure and analytics pipelines. Your work will contribute directly to the efficiency and effectiveness of our compliance management technology, enabling us to better serve our clients and drive innovation. You will contribute to the delivery of key datasets and reports, ensuring data quality and accessibility.

Key Responsibilities include, but are not limited to:

1. Develop and maintain robust and scalable data pipelines to extract, transform, and load (ETL) data from various sources into our data warehouse.
2. Design, build, and optimize data models to support analytical needs and reporting requirements.
3. Collaborate with data scientists to implement and deploy machine learning models and analytical solutions.
4. Monitor data quality and identify and resolve data integrity issues.
5. Contribute to the development of data documentation and metadata management practices.
6. Work with stakeholders to understand their data needs and translate them into technical requirements.
7. Assist in the evaluation and implementation of new data technologies and tools.
8. Participate in code reviews and contribute to the development of coding standards and best practices.
9. Independently manage assigned tasks and projects, ensuring timely delivery and quality results.
10. Proactively identify opportunities to improve data processes and systems.

Qualifications & Desired Skills:

1. Bachelor's degree in Computer Science, Data Science, Statistics, or a related field.
2. 4+ years of experience in data engineering, analytics engineering, or a similar role.
3. Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL).
4. Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and related data warehousing services (e.g., Snowflake, Redshift, BigQuery).
5. Familiarity with data testing frameworks.
6. Experience with ETL tools and techniques (e.g., Apache Airflow, dbt).
7. Solid understanding of data modeling principles and data warehouse architecture.
8. Strong analytical and problem-solving skills.
9. Experience with at least one programming language (e.g., Python, Java).
10. Good communication and collaboration skills.
11. Proficiency in using Git for version control and collaboration on codebase.

We are an equal opportunity employer and value diversity at Propelus. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Candidates from all backgrounds are encouraged to apply.

Full-time positions are scheduled to work 40 hours per week, M-F unless required otherwise by projects. Part-time positions are scheduled to work a maximum of 30 hours per week. Equipment, benefits, and perks are not provided to part-time or temporary employees.