Senior Data Analyst

ContexturePhoenix, AZ
Hybrid

About The Position

The Senior Data Analyst will work as part of the Data Services & Business Intelligence team to derive business value from enterprise data by implementing data analysis and reporting specifications provided by the Data Architect and Director of Data Services & Business Intelligence, including data transformations, consumption, and automation. This role will work with multiple healthcare data sources and cross-functional teams to establish integrated datasets across legacy and greenfield data/platforms. You will work closely with data producers, consumers, and subject matter experts to enhance data service capabilities by implementing data architecture frameworks, standards, and principals, including modeling, metadata, security, and reference data. This position is based in Phoenix Arizona; Denver Colorado; or Grand Junction, Colorado and requires local residency in one of these base locations. Our strategic flexibility allows for local work from home opportunities.

Requirements

  • Demonstrated experience with relational and non-relational data storage models, schemas, and structures used in data lakes and warehouses for big data, business intelligence, reporting, visualization, and analytics.
  • Hands-on experience with data extraction from data sources using analysis tools and programming languages, specifically Python and SQL.
  • Ability to understand and analyze various data domains, including clinical, claims, social determinants of health (SDOH), financial, and operational data.
  • Practical experience with industry-accepted standards, best practices, and principles for implementing well-designed data analysis and reporting solutions.
  • Data processing experience in a production environment with terabyte-sized datasets that are both structured and unstructured data
  • Required Languages: Python and SQL
  • Required Libraries: PyData stack
  • Data storage experience with Microsoft SQL Server, MongoDB, and Snowflake
  • Leveraging data partitioning, parallelization, and data flow optimization principles
  • SQL query development using query planning and optimization techniques
  • File manipulation across varied file types, encodings, formats, and standards
  • Secure Software Development Lifecycle (SSDLC), version control, and release management
  • Knowledge of healthcare interoperability standards such as HL7 (Health Level 7), FHIR (Fast Healthcare Interoperability Resources), CDA (Clinical Document Architecture), etc.
  • Knowledge of healthcare clinical code sets such as LOINC, SNOMED, CPT, ICD-10, etc.
  • Strong understanding of project management disciplines such as Agile and Waterfall.
  • Ability to translate technical requirements into actionable tasks for execution.
  • Ability to work in a fast-paced and rapidly changing environment while consistently meeting strict service level agreement performance requirements.
  • Ability to work independently as well as ability to effectively work in a team environment and maintain strong working relationships.
  • Working knowledge of Microsoft Office 365 toolset (OneDrive, Word, Excel, and PowerPoint).
  • Minimum of 5+ years of experience working in data-related positions with increasing responsibility and scope of duties; specifically, 5+ years working with relational databases, 4+ years working with analytical data workloads.
  • Bachelor’s Degree is required with a concentration in a data-related field such as Computer Science, Informatics, Mathematics, Engineering, etc.

Nice To Haves

  • M aster’s Degree is preferred.

Responsibilities

  • Develop, implement, and maintain data analysis and reporting solutions for data business intelligence, reporting, visualization, and analysis.
  • Support internal and external customers in data analysis and reporting activities, including data validation and in-depth analysis of source data.
  • Assist with the development, implementation, and maintenance of enterprise data management solutions.
  • Develop an expert understanding of internal enterprise data sources.
  • Transform data using industry-standard techniques such as standardization, normalization, de-duplication, filtering, projection, and aggregation.
  • Extract data from enterprise data sources as part of automated consumption data flows.
  • Conduct research and evaluation of data analysis and data measurement methodologies, technologies, and tools and make recommendations for implementation.
  • Prepare and present data analysis findings to internal and external stakeholders .
  • Collaborate with data producers, consumers, and subject matter experts to ensure smooth dissemination and flow of data within the organization.
  • Performs other related duties as assigned.

Benefits

  • Comprehensive benefits package
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service