Senior Data Engineer
Inactive
Fully remote work environment within the United States.Full-TimeSenior
This job is no longer active. We keep the page for reference, but the employer may not accept new applications.
Salary135,000 - 165,000 USD per year
Job Details
- Experience
- Minimum 5 years of professional data engineering experience, including at least 2 years working within cloud-native environments.
- Required Skills
- DockerPythonSQLApache AirflowKubernetesSnowflakeTerraformBigQuerydbt
Requirements
- Minimum 5 years of professional data engineering experience.
- Minimum 2 years of experience working within cloud-native environments.
- Advanced proficiency in Python and SQL.
- Hands-on experience with modern cloud data warehouse platforms such as BigQuery, Snowflake, or Amazon Redshift.
- Strong experience with data transformation frameworks including dbt.
- Expertise with workflow orchestration platforms such as Apache Airflow, Prefect, or Dagster.
- Proficiency with infrastructure-as-code tools like Terraform.
- Experience with containerization platforms such as Docker and Kubernetes.
- Strong understanding of data modeling methodologies including dimensional modeling and Data Vault.
- Knowledge of healthcare interoperability standards (HL7, FHIR, ICD-10, SNOMED CT, LOINC) and HIPAA compliance.
- Experience designing and supporting data governance and access management frameworks.
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.
Responsibilities
- Design, develop, and maintain scalable ELT/ETL pipelines that ingest and process structured and unstructured healthcare, claims, operational, and third-party data.
- 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.
- Implement modern data lake and lakehouse architectures.
- Ensure compliance with healthcare privacy and security regulations through the implementation of data governance, auditing, and access control.
- Establish data quality standards, monitoring frameworks, and testing strategies.
- Collaborate with cross-functional teams to design datasets, feature stores, and data products.
- Provide technical leadership and mentor junior engineers.