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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GCP Data Engineer - **Company:** Intersources Inc. - **Location:** Phoenix, AZ, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Adobe InDesign, Airflow, Business Analytics Applications, Big Data, BigQuery, Cloud Database, Cloud Storage, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, DevOps, Data Flow Control, Python (Programming Language), Meta-Data Management, Cloudera, Data Lakes, Information Technology, Data Analytics, Apache Kafka, Splunk, Data Pipelines - **Published:** August 7, 2026 - **Apply:** https://www2.jobdiva.com/portal/?a=62jdnw10t7d77ytz0lbaey9qxonk3b05a9tqw96rb7z6hlfo7xj79l9g6mp6aj2o&compid=0/jobs/22802607#/jobs/22802607 ## About the Role * 6+ years of experience in Data Engineering with an emphasis on Data Warehousing and Data Analytics * 4+ years of experience with one of the leading public clouds * 4+ years of experience in design and build of salable data pipelines that deal with extraction, transformation, and loading * 4+ years of experience with Python, Scala with working knowledge on Notebooks * 3+ years hands on experience on GCP Cloud data implementation projects (Dataflow, DataProc, Cloud Composer, Big Query, Cloud Storage, GKE, Airflow, etc.) * At least 2 years of experience in Data governance and Metadata Management * Ability to work independently, solve problems, update the stake holders * Analyze, design, develop and deploy solutions as per business requirements * Strong understanding of relational and dimensional data modeling * Experience in DevOps and CI/CD related technologies * Bachelor's Degree in Computer Science, Information Technology, Engineering, or related field * Excellent written, verbal communication skills, including experience in technical documentation and ability to communicate with senior business managers and executives * Excellent analytical, problem solving, and troubleshooting skills in large data warehousing environments ## Description * A solid experience and understanding of considerations for large-scale solutioning and operationalization of data warehouses, data lakes and analytics platforms on GCP is a must * Monitors the Data Lake constantly and ensures that the appropriate support teams are engaged at the right times * Design, build and test scalable data ingestion pipelines, perform end to end automation of ETL process for various datasets that are being ingested * Determine best way to extract application telemetry data, structure it, send to proper tool for reporting (Kafka, Splunk) * Create reports to monitor usage data for billing and SLA tracking * Work with business and cross-functional teams to gather and document requirements to meet business needs * Provide support as required to ensure the availability and performance of ETL/ELT jobs * Provide technical assistance and cross training to business and internal team members * Collaborate with business partners for continuous improvement opportunities ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Got AI ideas but no money? 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