Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Remote mid-level generalist Data Engineer with broad cloud and Spark requirements attracts high candidate density.
Core data engineering skills are highly transferable, though healthcare domain preference moderately increases specialization.
Explicit 5+ years requirement and mandatory Spark, Snowflake/Databricks, cloud, and SQL/Python make filters strict.
Design, build, and maintain scalable ETL/ELT data pipelines and cloud-based data platforms using tools like Snowflake, Databricks, Python, SQL, and Spark.
Develop and optimize data ingestion, modeling, and processing workflows to support AI, analytics, and healthcare system integrations with a focus on performance, scalability, and cost efficiency.
Collaborate with US-based teams and customers to define data requirements, troubleshoot issues, and deliver production-ready solutions with strong technical ownership, including mentoring junior engineers.
5+ years of professional Data Engineering experience.
Advanced proficiency in SQL and Python with hands-on experience in production-grade ETL/ELT pipelines and Apache Spark/PySpark.
Experience with modern cloud data platforms (Snowflake or Databricks) and cloud services (AWS or Azure).
Must be comfortable working remotely primarily during EST/PST business hours.
Experienced in complex healthcare or enterprise data environments, comfortable handling large, messy datasets and integrating multiple data sources including APIs and third-party systems.
Strong ownership mindset with ability to independently gather requirements and deliver end-to-end data engineering solutions in fast-paced settings.
Able to engage directly with US customers and cross-functional teams to solve problems and guide junior engineers, thriving in remote collaboration during US time zones.