Data Engineer

Definitive Healthcare

. Build, maintain, test, and support moderate-complexity ETL/ELT pipelines, transformations, and data components using Python, SQL, Spark/PySpark, and related technologies .

Posted 10/26/2026full-timeRemote • United StatesJuniorMid-Level💰 $93,000 - $141,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining ETL/ELT pipelines using Python and SQL, with a strong focus on data quality, performance optimization, and collaboration across teams. Proficient in modern data platforms and cloud technologies, ensuring reliable data solutions in production environments.

Highest-signal resume keywords

Python ProficiencySQL ProficiencyApache Spark/PySpark ExperienceCloud Platform Experience (AWS, Azure, GCP)Data Engineering Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT Pipeline DevelopmentData ModelingCode ReviewCI/CD PracticesObservabilityWorkflow Orchestration (Airflow, Argo)Relational DatabasesData Quality StandardsPerformance TroubleshootingTechnical Documentation

Soft Skills

Effective CollaborationProblem-SolvingCommunication SkillsKnowledge SharingConstructive Feedback

Tools & Technologies

DatabricksSnowflakeDelta LakeAI-Assisted Development ToolsKubernetes

Certifications & Qualifications

Bachelor's Degree in Computer Science, Engineering, or Information Systems

Industry Keywords

Healthcare Data ExperienceClaims DataConsumer DataData Processing TechnologiesVendor-Delivered Datasets

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCloudETLGoogle Cloud PlatformKubernetesPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Build, maintain, test, and support moderate-complexity ETL/ELT pipelines, transformations, and data components using Python, SQL, Spark/PySpark, and related technologies
Own defined pipeline components from implementation through testing, deployment, documentation, and production support
Troubleshoot pipeline failures, data quality issues, and performance problems; identify root causes and implement practical fixes
Contribute to component-level technical designs, estimates, and implementation plans
Apply practices for data modeling, testing, code review, observability, security, source control, CI/CD, and operational support
Monitor pipeline performance and reliability; identify opportunities to improve quality, efficiency, and maintainability
Develop working knowledge of Claims and Consumer data structures, transformations, dependencies, and data quality standards
Collaborate with engineers, QA, analysts, Product, Support, and data consumers to clarify requirements, resolve issues, and deliver reliable data changes
Assess downstream impacts of data and schema changes and support vendor-delivered data sources and customer issues
Participate in code reviews, pairing, sprint activities, technical discussions, documentation, and knowledge sharing
Support peers and less-experienced engineers through knowledge sharing and constructive review feedback
Use approved AI-assisted development tools responsibly to improve productivity, documentation, test coverage, and code quality

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
2+ years of Data Engineering, Software Engineering, or related experience building and supporting production data solutions
Proficiency in Python and SQL, with hands-on experience developing and maintaining production data pipelines
Experience with Apache Spark/PySpark or equivalent distributed data processing technologies
Experience with cloud platforms such as AWS, Azure, or GCP
Experience with modern data platforms such as Databricks, Snowflake, Delta Lake, or equivalent technologies
Experience with workflow orchestration technologies such as Airflow, Argo, or equivalent platforms
Working knowledge of relational databases, data modeling, testing, code review, observability, source control, CI/CD, and production support practices
Ability to own defined technical work, troubleshoot issues, collaborate effectively, and communicate progress, risks, and blockers
Preferred: healthcare data experience, including claims, pharmacy, eligibility, consumer, provider, or reference data
Preferred: experience processing large datasets using lakehouse or medallion architecture patterns
Preferred: experience deploying, operating, or supporting Spark workloads in Kubernetes or similar containerized environments
Preferred: experience supporting enterprise data products, analytics platforms, or business-critical data services in regulated environments
Preferred: experience onboarding or supporting vendor-delivered datasets and evaluating schema or downstream consumer impacts
Preferred: experience using AI-assisted engineering tools to improve development productivity, testing, documentation, and code quality

Benefits

Comp & perks

Company bonus or commission plan eligibility, depending on position
Medical coverage
Dental coverage
Vision coverage
Unlimited paid time off
401(k) plan with employer contribution
Industry leading products
Flexible and dynamic culture
Definitive Cares community service group
Competitive benefits package
401(k) match