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Healthfirst

Senior Data Engineer

Healthfirst

. Design and implement ELT/ETL solutions for batch and streaming ingestion, integration, refinement, and publish patterns on the Lakehouse .

Posted 10/7/2026full-timeRemote • Florida • United StatesSenior💰 $119,600 - $177,905 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing ELT/ETL solutions, developing scalable data pipelines using Python and PySpark, and applying DataOps practices for efficient data management. Proficient in cloud technologies, data warehousing concepts, and ensuring data quality and compliance.

Highest-signal resume keywords
Python DevelopmentPySpark FrameworkAWS GlueData Warehousing ConceptsDataOps Practices

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
ELT SolutionsETL SolutionsData Pipeline DevelopmentSQL ExpertiseData Quality ChecksDimensional ModelingCloud MigrationAutomated TestingGit-Based DevelopmentApache Spark
Soft Skills
Analytical SkillsProblem-Solving SkillsCommunication SkillsMentoringTechnical Leadership
Tools & Technologies
AWSMicrosoft AzureGoogle Cloud PlatformApache IcebergTerraformAirflowKafkaKinesisRESTful APIsAmazon EMR
Industry Keywords
DataOpsGovernanceMetadata ManagementHealthcare Regulatory ComplianceHIPAAPHI

Tech Stack

Tools & technologies
AirflowApacheAWSAzureCloudETLGoogle Cloud PlatformHadoopKafkaNoSQLPySparkPythonSparkSQLTerraform

About the role

Key responsibilities & impact
  • Design and implement ELT/ETL solutions for batch and streaming ingestion, integration, refinement, and publish patterns on the Lakehouse
  • Develop reusable data processing frameworks and configuration-driven pipelines using Python and PySpark
  • Build and maintain scalable orchestration workflows for production data delivery, including retries, historical loads, and operational runbooks
  • Implement data quality checks, validation frameworks, and monitoring against defined contracts and SLAs
  • Apply DataOps practices, including Git-based development, CI/CD/CT, automated testing, and controlled environment promotion
  • Contribute to data lifecycle practices, retention, archival, disaster recovery, and resiliency
  • Support platform modernization and cloud migration of legacy data flows into Lakehouse patterns
  • Collaborate with stakeholders to map technical designs to business processes, non-functional requirements, and consumption needs
  • Establish and document engineering standards, naming conventions, and practices; participate in Agile ceremonies and cross-team delivery
  • Provide technical leadership through mentoring, design and code reviews, and improvements to reliability, performance, and cost efficiency
  • Own reliable datasets supporting analytics and reporting across the governed Lakehouse

Requirements

What you’ll need
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent work experience
  • 8+ years of overall IT experience
  • 5+ years of hands-on experience designing and developing enterprise-scale data engineering solutions
  • Strong experience developing scalable data pipelines and reusable frameworks using Python and PySpark
  • Experience with AWS Glue, dbt, Apache Spark, or comparable technologies
  • Strong understanding of data warehousing concepts, dimensional modeling, and modern data lake/Lakehouse architectures
  • Experience with AWS, Microsoft Azure, or Google Cloud Platform; AWS preferred
  • Strong SQL expertise with relational databases; familiarity with NoSQL databases is a plus
  • Experience with Apache Spark, Amazon EMR, or Hadoop-based platforms
  • Experience using Git-based source control and Agile software development methodologies
  • Strong analytical, problem-solving, and communication skills
  • Preferred: AWS cloud-native data platforms, Apache Iceberg, CI/CD, DataOps, Terraform, Airflow/MWAA/Step Functions, RESTful APIs, Kafka/Kinesis/Spark Structured Streaming, data quality and observability, governance and metadata management, security and healthcare regulatory compliance (HIPAA/PHI), workload optimization, mentoring, design and code reviews

Benefits

Comp & perks
  • Medical, dental, and vision coverage
  • Incentive and recognition programs
  • Life insurance
  • 401k contributions
  • Competitive compensation and benefits package