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Data Engineer
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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.
2–4+ 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.
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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