Data Analytics Engineer

• Develop, implement, and maintain scalable ETL-Extract, Transform, and Load-pipelines that support efficient and reliable data movement across systems.
• Design, build, and optimize data models and data warehouse solutions using dimensional modeling principles to improve query performance, reporting accuracy, and data usability.
• Manage and analyze large-scale datasets using big data and cloud technologies such as Apache Spark, Hadoop, Apache Hive, Azure Data Lake, AWS, and related platforms.
• Collaborate with business leaders, analysts, product teams, and technical stakeholders to gather requirements and translate business needs into clear technical specifications.
• Develop dashboards, reports, and visualizations using business intelligence tools such as Looker to communicate insights clearly and effectively.
• Write and optimize complex SQL queries across platforms such as Microsoft SQL Server, Oracle, Snowflake, and cloud-based databases.
• Develop Python scripts and shell scripts to automate reporting workflows, support data validation, streamline recurring processes, and assist with advanced analytics initiatives.
• Define, calculate, document, and validate key performance indicators and business metrics.
• Calculate healthcare and employee-benefit metrics such as PEPM-per employee per month-and PMPM-per member per month.
• Clearly articulate the methodology used to calculate PEPM and PMPM metrics, including data sources, population definitions, eligibility rules, time periods, exclusions, assumptions, validation steps, and the reasoning behind the final calculation.
• Investigate data discrepancies, validate analytical outputs, document assumptions, and ensure that reporting results align with business expectations.
• Maintain clear documentation of data definitions, reporting logic, calculations, workflows, and technical processes.
• Participate effectively within an Agile development environment while managing multiple priorities and projects., Our client offers the stability and industry knowledge of a mature, 10-year-old organization while maintaining the innovative and collaborative environment commonly associated with a growing technology company.

The company has developed a strong culture where employees are encouraged to contribute ideas, continue learning, collaborate across departments, and see the direct impact of their work.

This is an excellent opportunity for a data professional who enjoys solving complex business problems, developing reliable analytical solutions, and turning raw data into strategic assets that support better decisions.

Pay: $95,000.00 - $105,000.00 per year

Our client is seeking a dynamic, detail-oriented Data Analytics Engineer to join its innovative and collaborative team.

This is an opportunity to join a mature, established company with approximately 10 years of experience in the healthcare analytics and technology space. Our client has built a strong workplace culture centered on collaboration, innovation, continuous learning, and using data to create meaningful business outcomes.

In this role, the Data Analytics Engineer will use big data systems, cloud technologies, and advanced analytics tools to design, develop, and optimize data pipelines, data models, reporting solutions, and analytical processes. The successful candidate will help transform complex datasets into accurate, actionable insights that support strategic decision-making, business growth, and operational excellence.

The ideal candidate will combine strong technical skills with the ability to understand business questions, define meaningful metrics, validate results, and clearly communicate how conclusions were reached., * Proven experience in data analytics engineering, data engineering, business intelligence, software development, or a closely related field.

• Advanced SQL skills, including experience writing complex queries, validating results, analyzing large datasets, and working with relational databases.
• Hands-on experience using Python for data analysis, workflow automation, reporting, or data validation.
• Experience working within cloud platforms such as AWS or Microsoft Azure for data storage, processing, and analytics.
• Strong understanding of data warehouse architecture, data modeling, dimensional modeling, and database design principles.
• Experience developing and maintaining ETL or ELT pipelines using tools such as Informatica, Talend, Apache Spark, or comparable technologies.
• Familiarity with big data technologies, including Hadoop, Spark, Hive, Azure Data Lake, or similar platforms.
• Experience using business intelligence and visualization tools such as Looker or comparable reporting platforms.
• Demonstrated experience defining, calculating, validating, and documenting business metrics and KPIs.
• Experience calculating PEPM or PMPM metrics, with the ability to clearly explain the full calculation process and methodology.
• Strong analytical and problem-solving skills, with close attention to data accuracy, consistency, and quality.
• Ability to translate business questions into clear, measurable, and technically sound analytical solutions.
• Strong written and verbal communication skills, including the ability to explain technical findings and metric logic to both technical and nontechnical stakeholders.
• Experience working in healthcare analytics, healthcare technology, employee benefits, health insurance, population health, or a healthcare SaaS environment is strongly preferred.
• Ability to work collaboratively within a fast-paced Agile environment while effectively managing multiple projects and priorities., * Do you have experience building the measurement layer models rely on?
• Do you have experience calculating healthcare and employee-benefit metrics such as PEPM-per employee per month-and PMPM-per member per month?

Experience:

• analytics engineering: 3 years (Required)

$95,000 - $105,000 a year - Full-time, Pulled from the full job description

• 401(k)
• Health insurance
• Paid time off, * 401(k)
• Health insurance
• Paid time off