Abacus Insights-posted 3 months ago
101-250 employees

Abacus Insights is a mission-driven, start-up technology company focused on transforming the healthcare payer industry, ultimately creating a more personalized patient experience, improving health outcomes, and lowering the overall cost of healthcare. Abacus Insights provides a flexible, efficient, and secure platform that organizes and exchanges healthcare data from various sources and formats, allowing our customers to uncover differentiated insights that address their clients' needs. Our employees know that they play an active role in keeping our customers' data safe and are responsible for ensuring that our comprehensive policies and practices are met. With our deep expertise in cloud-enabled technologies and knowledge of the healthcare industry, we have built an innovative data integration and management platform that allows healthcare payers access to data that has been historically siloed and inaccessible. Through our platform, these health insurance payers can ingest and manage all the data they need to transform their business by supporting their analytical, operational, and financial needs. Since our founding in 2017, Abacus has built a highly successful SaaS business, raising more than $81 Million by leading VC firms who have deep expertise in the healthcare and technology industries. We are solving problems of massive scale and complexity in an industry that is not only ready for disruption. We're growing quickly and would love for you to be a part of it!

  • Identify and define requirements for canonical data models, consumption use cases, metadata, semantics layer, and ontologies required by enterprise healthcare customers.
  • Use Databricks Unity Catalog to build a semantic layer, manage AI assets and registered metric definitions.
  • Leverage AI Assistant and SQL Agents to build and test the semantic layer.
  • Build conceptual, logical and physical data models aligned with enterprise architecture, business requirements and industry standards.
  • Follow data modeling best practices, including schema evolution, lossless data modeling, metadata management, and data versioning.
  • Use enterprise data modeling tools (Erwin, ER/Studio, DBT, or similar).
  • Ensure models support analytical (data science, actuarial, reporting) and operational (Claims, Care Management) use cases.
  • Maintain metadata, business glossary, entity relationship diagrams and data dictionaries to support data lineage and governance.
  • Partner with Client Management, Product, and Business Analyst teams to understand client needs, assess data model impact, and ensure data models and related artifacts meet or exceed expectations.
  • Work with client management teams to provide support and data model expertise during client implementation.
  • Perform data profiling analysis.
  • Use SQL, data modeling and data integrity principles.
  • Strong hands-on experience with Databricks Unity Catalog, cloud data platforms (Databricks, Snowflake) and data Lakehouse architectures.
  • Healthcare reporting or data engineering experience.
  • Experience with data governance, security, and regulatory compliance in healthcare data management.
  • 2+ years of experience in data modeling, and cloud-based data engineering or reporting.
  • Experience with enterprise data modeling tools (Erwin, ER/Studio, DBSchema, or similar).
  • Understanding of healthcare data across Core Payer (Claims, Membership, Enrollment, Provider, Billing, Premium) and Clinical Interoperability (FHIR, HL7, ADT, CCDA, etc.) domains.
  • Experience with schema evolution, lossless data modeling, and data versioning strategies.
  • Strong background in SQL, data profiling, and metadata creation and maintenance.
  • Ability to learn from senior modelers, enforce modeling best practices, and drive adoption of enterprise data standards.
  • Excellent collaboration skills to work with data architects, engineers, and client implementation teams.
  • NoSQL data model experience.
  • Python coding skills.
  • Knowledge of APIs, SDKs, and distributed data frameworks for enabling real-time and micro-batch processing of structured, semi-structured and unstructured data.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service