About the role

Apixio is looking for a Senior Analytics Engineer to join our analytics team. This role will primarily be responsible for building out our analytics platform on Databricks, using dbt and Python for data transformations. The duties of the Senior Analytics Engineer will comprise data discovery, data modeling, data engineering, and data governance, thus serving as a full-stack analytics engineer leveraging the modern data stack. This is a foundational role within a small, talented team with the opportunity to make a huge impact in a growing organization.

Who you areData Discovery and Data Modeling

• Conduct thorough data discovery to identify and understand the organization's data sources, adhering to data quality and data governance policies.
• Collaborate with stakeholders across Apixio (Ops, Product, Marketing, G&A) and within the team to understand business requirements and translate them into data models that effectively capture data and transform them into metrics.
• Design and implement data models using Databricks Delta Lake, ensuring data integrity, consistency, and scalability.
• Document data models and data governance processes to maintain knowledge transfer and ensure data quality standards.

Data Engineering and Transformation

• Develop and implement data pipelines using Databricks and dbt to collect, process, and transform data from various sources.
• Utilize dbt to automate and streamline ELT processes, ensuring data quality and consistency.
• Implement data quality checks and data cleansing techniques to ensure data accuracy and consistency.
• Optimize data pipelines for performance and scalability to handle large volumes of data.

Data Visualization and Insights

• Develop and maintain data visualizations and dashboards using tools like Looker.
• Create interactive dashboards that provide business users with self-service access to data insights.
• Communicate data insights effectively to stakeholders, translating technical concepts into clear and actionable recommendations.

What you bring to the table

• 5+ years Data Engineering experience including
• 3+ years hands-on experience working with large, structured/unstructured datasets using partitioned cloud storage architecture using query engines such as Spark, Delta Lake.
• 3+ years experience designing, developing, deploying and testing in Databricks. 
• 3+ years of hands-on experience in Python/Pyspark/SparkSQL.
• 2+ years experience on Big data pipelines/DAG tools like Airflow, dbt is required.
• 2+ years of SQL experience, specifically to write complex, highly optimized queries across large volumes of data.
• Experience in the AWS computing environment and storage services such as s3/glacier is required.
• Experience with conceptual, logical and/or physical database designs is required.
• Good knowledge in Linux and shell scripting is highly desired.
• Past experience in healthcare data extraction, transformation and normalization is highly desired.
• Hands-on experience with Kafka or other live streaming technology is highly desired.
• Experience with Data Visualization tools like Looker / Tableau is desired.
• Ability to lead and complete projects independently once given objective and direction.
• Ability to independently look for resourceful solutions and enhancements; and communicate any issues timely if they arise, and present solutions to the problems.
• Strong communication skills to partner with data integration, engineering, DevOps, customer success, and product teams and collect technical and business requirements.
• High agency, integrity, ownership, and curiosity.

What success looks like

• In 1 month: you have understood the various data sources across Apixio
• In 3 months: you have built data pipelines to bring more data into the analytics platform
• In 6 months: you have led 2-3 projects working with stakeholders end-to-end, going from requirements to KPI / dashboard delivery