Senior Data Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Data Engineer in the United States.

Join a high-impact data engineering team focused on building scalable cloud-based data platforms that power advanced analytics, artificial intelligence, and machine learning solutions within the healthcare industry. In this role, you will design and maintain robust data pipelines, architect modern cloud infrastructure, and ensure the reliability, security, and quality of large-scale healthcare datasets. You will collaborate closely with data scientists, machine learning engineers, analysts, and business stakeholders to transform complex data into actionable insights. This position offers the opportunity to work with cutting-edge technologies in a mission-driven environment where innovation, technical excellence, and continuous improvement are highly valued. If you are passionate about cloud-native data engineering and solving complex data challenges at scale, this role provides an exciting opportunity to make a meaningful impact.

Accountabilities

• Design, develop, and maintain scalable ELT/ETL pipelines that ingest and process structured and unstructured healthcare, claims, operational, and third-party data from a variety of sources.
• Build and optimize cloud-based data warehouse solutions to support reporting, analytics, machine learning, and business intelligence initiatives.
• Develop and manage workflow orchestration frameworks that ensure reliable, observable, and highly available data processing pipelines.
• Create and support real-time and streaming data architectures to enable timely data delivery and advanced analytical use cases.
• Architect, deploy, and manage cloud-native data infrastructure using infrastructure-as-code methodologies while optimizing performance, scalability, and cost efficiency.
• Implement modern data lake and lakehouse architectures capable of supporting large-scale healthcare datasets and mixed data formats.
• Ensure compliance with healthcare privacy and security regulations through the implementation of data governance, auditing, masking, de-identification, and access control practices.
• Establish data quality standards, monitoring frameworks, observability solutions, and testing strategies to proactively identify and resolve data issues.
• Collaborate with cross-functional teams to design datasets, feature stores, and data products that support machine learning and clinical decision-support initiatives.
• Provide technical leadership, mentor junior engineers, participate in architectural discussions, and contribute to engineering best practices and CI/CD adoption.
  
  

Requirements

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• Minimum 5 years of professional data engineering experience, including at least 2 years working within cloud-native environments.
• Advanced proficiency in Python and SQL for developing, optimizing, and maintaining data pipelines and transformation workflows.
• Hands-on experience with modern cloud data warehouse platforms such as BigQuery, Snowflake, or Amazon Redshift.
• Strong experience with data transformation frameworks including dbt or comparable solutions.
• Expertise with workflow orchestration platforms such as Apache Airflow, Prefect, or Dagster.
• Proficiency with infrastructure-as-code tools, including Terraform or equivalent technologies, and containerization platforms such as Docker and Kubernetes.
• Strong understanding of data modeling methodologies, including dimensional modeling and Data Vault architecture.
• Knowledge of healthcare interoperability standards such as HL7, FHIR, ICD-10, SNOMED CT, and LOINC, along with familiarity with HIPAA and healthcare data compliance requirements.
• Experience designing and supporting data governance, lineage, cataloging, and access management frameworks.
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field; Master’s degree is a plus.
• Experience with Electronic Health Record (EHR) systems, healthcare APIs, streaming technologies, cloud healthcare platforms, machine learning infrastructure, or MLOps environments is highly desirable.
• Strong analytical thinking, communication skills, problem-solving abilities, and a collaborative mindset.
  
  

Benefits

• Competitive annual salary ranging from $135,000 to $165,000, based on experience, qualifications, skills, and geographic location.
• Fully remote work environment within the United States.

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• Comprehensive healthcare coverage.
• 401(k) retirement savings plan.
• Paid time off and company-sponsored leave programs.
• Opportunity to work with modern cloud technologies, AI-driven platforms, and large-scale healthcare datasets.
• Career growth opportunities within a rapidly evolving and innovative technology environment.
• Exposure to advanced machine learning, data engineering, and cloud architecture initiatives.
• Collaborative and supportive team culture focused on continuous learning and professional development.
• Travel opportunities for business-related activities and team collaboration, as needed.
  
  

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.