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Senior Staff - GCP Data Engineer

Build scalable data pipelines on GCP for business insights

Design and maintain end-to-end data engineering solutions on Google Cloud Platform, including ETL/ELT pipelines, real-time streaming, and data lake architectures.

Why This Role?

Direct impact on Equinix's data infrastructure and analytics

Required Skills

gcpdata engineeringetleltcloud dataflowcloud composerbigqueryGoogle Cloud PlatformETL/ELT PipelinesData WarehousingData Modeling

Indonesia Context

Working Hours Overlap:
Flexible — work your own hours

Keywords

GCP Data EngineerCloud DataflowApache AirflowBigQueryData LakeData WarehouseETL Pipelines
View Original Description from The Muse

Original description from The Muse

Who are we? Equinix is the world's digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future. Help us challenge assumptions, uncover bias, and remove barriers-because progress starts with fresh ideas. You'll find belonging, purpose, and a team that welcomes you-because when you feel valued, you're empowered to do your best work. ob Summary As a key member of the Data Team at Equinix, we are seeking a skilled GCP Data Engineer who will be responsible for end-to-end development of Data Engineering use cases, Equinix Data Lake platform and tools. You will design, build, and maintain scalable data infrastructure and analytics solutions on Google Cloud Platform. The ideal candidate will have strong expertise in cloud-native data technologies and a passion for building robust, efficient data pipelines that drive business insights. Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines using Cloud Dataflow, Cloud Composer (Apache Airflow), Dataform/dbt and Cloud Functions Build real-time streaming data pipelines using Cloud Pub/Sub, Kafka and Dataflow Implement automated data quality checks and monitoring across all data workflows Optimize pipeline performance and cost efficiency through proper resource allocation and scheduling Architect and implement data lake and data warehouse solutions using Dataproc, BigQuery, Cloud Storage, and Cloud SQL Design optimal data models, partitioning strategies, and clustering for analytical workloads Manage data lifecycle policies and implement automated archival and retention strategies Ensure data security, encryption, and access control across all storage layers Build and optimize BigQuery datasets for analytics and reporting use cases Create and maintain dimensional models and fact tables for business intelligence Implement data marts and aggregation layers for improved query performance Support self-service analytics through proper data cataloging and documentation Having good knowledge of Dataplex and Analytics hub Integrate data from various sources including databases, APIs, SaaS applications, and file systems Implement change data capture (CDC) solutions for real-time data synchronization Work with third-party data providers and external data feeds Implement comprehensive monitoring and alerting using Cloud Monitoring and Cloud Logging Troubleshoot data pipeline issues and implement robust error handling mechanisms Maintain data lineage documentation and impact analysis capabilities Qualifications Technical Skills GCP Services: 6+ years hands-on experience with BigQuery, Cloud Dataflow Cloud Composer, Cloud Storage, Cloud Pub/Sub, Dataform/dbt and Cloud Functions Programming: Proficiency in Python/Java and SQL; experience with Spark/Beam development Data Technologies: Strong understanding of Apache Beam, Apache Airflow, and distributed computing concepts Database Systems: Experience with both RDBMS (Cloud SQL, PostgreSQL, MySQL) and NoSQL (Bigtable, Firestore) databases Infrastructure as Code: Experience with Terraform, Cloud Deployment Manager, or similar tools Professional Experience Bachelor's degree in computer science, Engineering, or related field 7+ years of experience in data engineering or related roles 6+ years of specific experience with Google Cloud Platform Experience with version control systems (Git) and CI/CD pipelines Knowledge of data modelling techniques and dimensional modelling Preferred Qualifications Google Cloud Professional Data Engineer certification Experience with containerization (Docker, Kubernetes/GKE) Experience with data governance and compliance frameworks (GDPR, HIPAA, SOX) Familiarity with business intelligence tools (Looker, Tableau, Power BI) Experience with streaming technologies beyond GCP (Kafka, Spark Streaming) Equinix is committed to

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Source
The Muse
Job Type
full time
Location
Worldwide Remote · Remote
Category
Data & Analytics
Seniority
senior
PostedNew
Jun 4, 2026

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