Overview
Skills
Job Details
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Design and architect end-to-end data solutions using Google Cloud Platform services like BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Dataproc.
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Build and optimize scalable ETL/ELT pipelines to support data ingestion, transformation, and processing.
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Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver reliable data solutions.
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Ensure data governance, quality, security, and compliance across the architecture.
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Implement data modeling best practices for structured and unstructured data sources.
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Automate infrastructure using Terraform or Deployment Manager for consistent and repeatable deployments.
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Monitor and troubleshoot data pipeline issues and optimize performance and cost-efficiency.
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Lead the evaluation and adoption of new tools, frameworks, and practices in the Google Cloud Platform ecosystem.
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Mentor junior data engineers and guide architectural decisions.
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Bachelor's or Master's degree in Computer Science, Engineering, or related field.
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6+ years of experience in data engineering with 2+ years in a cloud architecture role.
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Deep expertise in Google Cloud Platform services including BigQuery, Dataflow, Pub/Sub, Cloud Functions, and GCS.
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Strong proficiency in SQL, Python, and/or Java for data pipeline development.
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Experience with Apache Beam, Apache Spark, or other distributed data processing frameworks.
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Solid understanding of data warehousing, data lakes, and streaming/batch processing paradigms.
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Hands-on experience with CI/CD tools and Infrastructure as Code (IaC) like Terraform.
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Strong knowledge of data security and compliance practices (e.g., GDPR, HIPAA).