Job Description
About The Job
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
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 w...
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
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 w...
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