Senior Data Modeler
About the role
This role plays a critical part in designing, developing, and maintaining logical and physical data models, while also architecting, building, and optimizing the data pipelines and platforms that power our enterprise data warehouse, analytics ecosystem, and business intelligence solutions. This position ensures data assets are structured, engineered, and delivered in a scalable, high-performance, and user-friendly manner across the organization.
Responsibilities
- Data Modeling
- Design, implement, and optimize conceptual, logical, and physical data models to support enterprise reporting, analytics, and data science use cases.
- Partner with data engineers, business analysts, and stakeholders to translate business needs into robust data structures.
- Define and enforce data modeling standards, best practices, and naming conventions.
- Develop and maintain data dictionaries, ER diagrams, and metadata documentation.
- Evaluate existing data models and workflows to improve performance, scalability, and maintainability.
- Contribute to enterprise data architecture patterns and reusable modeling frameworks.
- Data Engineering & Platform Architecture
- Architect, build, and optimize scalable ETL/ELT pipelines using modern data engineering frameworks and cloud technologies.
- Lead the design and development of distributed data processing workflows using Databricks, PySpark, Azure SQL, and Azure Synapse.
- Develop data ingestion frameworks (batch and streaming) from FHIR, APIs, files, databases, and event streams.
- Ensure pipelines meet enterprise standards for reliability, performance, observability, and recoverability.
- Optimize SQL, PySpark, and Python workloads for analytics and downstream consumption.
- Oversee data lake and data warehouse architecture, including partitioning, schema evolution, delta lake management, and performance tuning.
- Troubleshoot and resolve complex data pipeline and platform issues across cloud environments.
- Mentor junior engineers and modelers, influencing engineering patterns and architectural direction.
- Collaborate with security teams to enforce access controls, encryption, secrets management, and compliance requirements.
Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Data Management, or equivalent experience.
- 7+ years of experience in data modeling, data engineering, dimensional modeling, or data architecture roles.
- Strong knowledge of relational, dimensional, and NoSQL data modeling techniques.
- Advanced SQL expertise and experience designing for cloud data platforms such as Databricks, Synapse, Azure SQL, Redshift, or BigQuery.
- Experience building scalable ETL/ELT pipelines using modern tools (Azure Data Factory, Databricks, Synapse Pipelines, SSIS, etc.).
- Proficiency with Python, PySpark, or Scala.
- Hands-on experience with Azure data services including Data Factory, Azure SQL, Synapse, Data Lake Storage Gen2, and Databricks.
- Experience designing and optimizing data lake and lakehouse architectures.
- Familiarity with CI/CD pipelines, Git workflows, and DevOps practices.
- Ability to influence dispersed teams and drive complex implementations.
- Strong attention to detail and organizational skills.
- Comfortable working cross-functionally in a dynamic, remote environment.
- Ability to balance near-term delivery with long-term platform evolution.
Preferred Experience
- Designing unified data platforms, semantic layers, ontologies, or knowledge graphs that support AI/ML initiatives.
- Experience with enterprise analytics and BI platforms such as Power BI, Tableau, Qlik, or Databricks AI/BI.
- Exposure to data governance, cataloging, and MDM practices.
- Knowledge of data vault, star schema, and snowflake modeling techniques.
- Experience with real-time or streaming data pipelines using Kafka, Event Hubs, or Spark Streaming.
- Familiarity with API platforms and tools such as Postman or API gateways.
- Experience tuning Spark workloads and managing cloud compute costs.
- Strong written and verbal communication skills across technical and non-technical audiences.
Benefits
Everforth Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Everforth Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Everforth Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Everforth Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our ‘Welcome Packet’ as well, which an Everforth Apex team member can provide.
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