Senior Analytics Engineer
Abarca Health- Full Time
- Senior (5 to 8 years)
Candidates should have at least 3 years of experience in analytics engineering, data engineering, or data analysis with a strong focus on building data pipelines and deriving insights. Advanced SQL skills for complex queries and performance optimization on large datasets are required. Experience with ELT/ETL and orchestration tools like Airflow is necessary, along with a solid foundation in data modeling principles. Candidates should possess strong problem-solving skills, attention to detail, and the ability to communicate complex technical information effectively. Bonus skills include experience with Python, AWS, and SparkSQL, as well as familiarity with medical healthcare claims data models.
As an Analytics Engineer, you will dive deep into data to reveal insights on product performance, customer behavior, claims patterns, and key financial metrics. You will develop and refine data models, transformations, and visualizations that support decision-making across teams. Additionally, you will design, build, and maintain scalable data pipelines using Airflow to ensure seamless data flow. Collaboration with product managers, data scientists, subject matter experts, and functional leads will be essential to understand data needs and deliver actionable insights.
AI-driven solutions for healthcare administration
Machinify provides AI-driven solutions to improve decision-making in the healthcare industry. Its platform helps health plans, payers, and providers optimize their operations, particularly in areas like claims processing and utilization management. The applications offered by Machinify can be quickly deployed, allowing clients to see immediate returns on investment. This focus on rapid implementation sets Machinify apart from competitors, as healthcare organizations increasingly seek cost efficiency and better patient outcomes. The company's goal is to enhance operational efficiency and help clients manage healthcare expenditures more effectively.