Role Overview :
We are looking for a skilled DataOps Engineer to operationalize and industrialize data pipelines in healthcare and medical environments. You will design, automate, and maintain reliable data flows from medical devices, EMS systems, and other healthcare sources into analytics and reporting platforms. This role applies DevOps principles to data, ensuring high data quality, observability, and rapid delivery of insights while meeting strict regulatory and uptime requirements.
Key Responsibilities :
- Design, build, deploy, and optimize end-to-end data pipelines (ingestion, transformation, orchestration, and delivery) using modern DataOps practices.
- Implement CI/CD pipelines for data workflows, including version control, automated testing, and deployment of transformations (e.g., using dbt).
- Orchestrate complex workflows with tools like Apache Airflow, Prefect, or cloud-native orchestrators.
- Establish monitoring, alerting, and observability for data pipelines — ensuring data freshness, quality, and lineage.
- Perform root-cause analysis on pipeline failures and implement preventive measures.
- Collaborate with data engineers, analysts, data scientists, and business stakeholders to translate requirements into reliable data products.
- Enforce data governance, quality frameworks, and compliance controls (HIPAA, PHI security) in all data processes.
- Automate infrastructure provisioning and support cloud data platforms (Azure, AWS, or GCP).
- Contribute to continuous improvement of DataOps processes, tools, and standards in the managed services environment.
- Participate in on-call rotation and maintain SLAs for data availability and performance.
Required Qualifications & Skills :
- 8 years of experience in data engineering or DataOps roles.
- Strong expertise in building and operating data pipelines (ETL/ELT) and orchestration tools.
- Proficiency in Python, SQL, and at least one cloud platform (Azure Synapse, AWS Glue, GCP Dataflow preferred).
- Hands-on experience with dbt, Airflow, Docker, Kubernetes, and Git.
- Experience with data quality, observability, and testing frameworks.
- Solid understanding of healthcare data concepts, compliance (HIPAA), and regulated environments.
- Excellent problem-solving, collaboration, and communication skills.
- Preferred Qualifications
- Experience supporting medical device, EMS, or healthcare analytics data.
- Certification in cloud data services or DataOps practices.
- Exposure to real-time streaming (Kafka, Spark Streaming) and modern data stacks (Databricks, Snowflake).