Data Engineer

contexture; Arizona; Hybrid; USD 110,000 - 160,000; Full time

Job summary

Contexture is seeking a Data Engineer to join the Data Operations & Engineering, Transformation and Analysis team in Phoenix, Denver, or Grand Junction. You’ll derive business value from enterprise data by implementing data architecture standards, modeling, and reference data across legacy and greenfield systems.

You will work with producers and consumers to enhance data service capabilities, including data storage, processing, and orchestration using tools like Prefect and Airflow, with a focus

Qualifications

• 4+ years in data-related roles with relational databases and analytical workloads.
• Experience with ETL, data lifecycle management, and data governance.
• Familiarity with healthcare interoperability standards (HL7, FHIR) is a plus.

Responsibilities

• Develop and maintain enterprise data management solutions for BI, reporting, and analytics.
• Design data processing flows from diverse sources and load into SQL Server, MongoDB, and Snowflake.
• Collaborate with cross-functional teams to implement data architecture standards and security.

Skills

Python

SQL

ETL

Data modeling

Metadata management

Data visualization

Prefect

Airflow

SSDLC

Healthcare data standards

Education

Bachelor’s Degree in data-related field

Tools

Microsoft SQL Server

MongoDB

Snowflake

Python libraries (PyData stack)

Job description

Summary

The Data Engineer will work as part of the Data Operations & Engineering, Transformation and Analysis team to derive business value from enterprise data by implementing technical specifications provided by the Data Architect and Director of Data Operations & Engineering, including data storage, processing, transformation, ingestion, 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 systems/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.

Qualifications

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skills, and/or abilities required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Essential Duties and Responsibilities

• Develop, implement, and maintain enterprise data management solutions to enable organizational business intelligence, reporting, visualization, and analysis.
• Assist with the development, implementation and maintenance of an overall organizational data strategy that is in line with business processes.
• Design and build data processing flows to extract data from various sources, such as databases, API endpoints, and flat files.
• Load data into data storage systems, specifically Microsoft SQL Server, MongoDB, and Snowflake.
• Transform data using industry‑standard techniques such as standardization, normalization, de‑duplication, filtering, projection, and aggregation.
• Build and maintain data processing environments, including hardware and software infrastructure. Working knowledge of data flow orchestration tools such as Prefect and Airflow is preferred.
• 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.

Skills

• 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 extract, transform, load (ETL) process design, data lifecycle management, metadata management, and data visualization/report generation.
• Practical experience with industry‑accepted standards, best practices, and principles for implementing a well‑designed enterprise data architecture.
• Technical Skills and Experience:
  • 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, Dask, and Prefect
  • Data storage experience with Microsoft SQL Server, MongoDB, and Snowflake
  • Leveraging data partitioning, parallelization, and data flow optimization principles
  • Implementing data sterilization, normalization, and standardization processes
  • Orchestrating fault tolerant/redundant data processing flows
  • SQL query planning and optimization for incremental and historical workloads
  • 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, FHIR, CDA, 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).

Education/Experience

• Minimum of 4+ years of experience working in data‑related positions with increasing responsibility and scope of duties; specifically, 4+ years working with relational databases, 3+ years working with analytical data workloads, and 2+ years working with batch data processing technologies.
• Bachelor’s Degree is required with a concentration in a data‑related field such as Computer Science, Informatics, Mathematics, Engineering, etc.

Work Environment

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The noise level in the work environment is usually moderate.

The position may require occasional availability for after‑hours work, outside of regularly scheduled hours.

The position may require ability to periodically drive to and from clients, conferences and / or events; and / or limited travel.

This position is expected to be exposed to, process, or handle sensitive information including but not limited to Protected Health Information (PHI), Personally Identifiable Information (PII), financial information, etc. As such, the holder of this position is expected to comply with all applicable laws, regulations, organizational policies, and compliance expectations.

Physical Demands

• Frequent communication and information exchange.
• Regular movement within the office to access equipment and materials.
• Ability to remain stationary for extended periods (approximately 50% of the time).
• Continuous use of computers and office equipment (e.g., keyboard, monitor, printer).
• Frequent handling of materials up to 10 lbs; occasional handling up to 30 lbs.

Benefits

Contexture provides a comprehensive benefits package. For details, please request a Benefit Summary from our Benefits Department.

The organization is an inclusive Equal Opportunity Employer. We do not discriminate on the basis of age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or other status protected by law or regulation.