Build and maintain data pipelines using Python and Apache Spark.
Orchestrate workflows using Airflow and Google Cloud Workflows (CloudFlow).
Develop deploy and manage containerized data services using Docker and Cloud Run.
Design optimize and monitor datasets and queries in BigQuery.
Ingest transform and integrate external data through REST APIs.
Manage data lifecycle and storage using Google Cloud Storage (GCS).
Implement data quality monitoring and observability best practices.
Collaborate with cross-functional engineering product and data science teams.
Requirements
24 years of experience as a Data Engineer or similar role.
Strong proficiency in Python SQL and Spark/PySpark.
Hands-on experience with Airflow and cloud-native orchestration (e.g. Cloud Workflows).
Experience with Docker containers and deploying services in Cloud Run.
Skilled with BigQuery GCS and general GCP data tooling.
Experience working with REST APIs and building ingestion integrations.
Solid understanding of data modeling ETL/ELT pipelines and distributed systems.
Bonus: Experience with healthcare data standards (FHIR HL7) or regulated environments.
Benefits
Competitive salary and performance-based incentives
Flexible work arrangements / hybrid work options
Paid time off and public holidays
Professional development opportunities (training workshops certifications)
Supportive collaborative and mission-driven work culture
Employee wellness programs and mental health support
Build and maintain data pipelines using Python and Apache Spark.Orchestrate workflows using Airflow and Google Cloud Workflows (CloudFlow).Develop deploy and manage containerized data services using Docker and Cloud Run.Design optimize and monitor datasets and queries in BigQuery.Ingest transform an...
Build and maintain data pipelines using Python and Apache Spark.
Orchestrate workflows using Airflow and Google Cloud Workflows (CloudFlow).
Develop deploy and manage containerized data services using Docker and Cloud Run.
Design optimize and monitor datasets and queries in BigQuery.
Ingest transform and integrate external data through REST APIs.
Manage data lifecycle and storage using Google Cloud Storage (GCS).
Implement data quality monitoring and observability best practices.
Collaborate with cross-functional engineering product and data science teams.
Requirements
24 years of experience as a Data Engineer or similar role.
Strong proficiency in Python SQL and Spark/PySpark.
Hands-on experience with Airflow and cloud-native orchestration (e.g. Cloud Workflows).
Experience with Docker containers and deploying services in Cloud Run.
Skilled with BigQuery GCS and general GCP data tooling.
Experience working with REST APIs and building ingestion integrations.
Solid understanding of data modeling ETL/ELT pipelines and distributed systems.
Bonus: Experience with healthcare data standards (FHIR HL7) or regulated environments.
Benefits
Competitive salary and performance-based incentives
Flexible work arrangements / hybrid work options
Paid time off and public holidays
Professional development opportunities (training workshops certifications)
Supportive collaborative and mission-driven work culture
Employee wellness programs and mental health support
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