Senior Data Engineer - GCP

Overview

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.

Job Summary

As a Senior Data Engineer at Equinix, you will be responsible for driving end-to-end delivery of enterprise-scale data solutions on Google Cloud Platform. This role combines hands-on technical expertise, requiring you to design sophisticated system architectures, lead cross-functional teams, and mentor Staff and other data engineers. You will be responsible for solution design and ensuring the successful delivery of mission-critical data products. The ideal candidate demonstrates exceptional technical depth in GCP data technologies, proven leadership in guiding engineering teams through complex challenges, and the ability to translate strategic business objectives into scalable, innovative technical solutions. Knowledge of AI, Machine Learning Operations, and emerging technologies like Agentic AI and Model Context Protocol (MCP) is highly valued.

Responsibilities

System Design & Architecture Leadership

• Architect complex, distributed data systems capable of handling petabyte-scale workloads with fault tolerance and high availability
• Design data platform architectures considering scalability, performance, cost optimization, and operational excellence
• Evaluate and recommend emerging technologies, tools, and architectural patterns to drive innovation
• Create comprehensive architectural documentation, design patterns, and best practices guidelines
  
  

Technical Solutioning & Delivery

• Own end-to-end delivery of complex data engineering initiatives from conception to production
• Design and implement sophisticated solutions leveraging BigQuery, Cloud Dataflow, Composer, Dataform/dbt, Pub/Sub, and Vertex AI
• Architect and build real-time streaming data pipelines using Cloud Pub/Sub, Kafka, and Apache Beam
• Develop advanced data transformation frameworks and custom processing engines
• Design microservices-based data platforms with containerization (Docker/Kubernetes)
• Establish comprehensive observability, monitoring, and alerting frameworks
• Drive performance optimization, cost management, and operational efficiency initiatives
  
  

Team Leadership & Mentorship

• Lead and mentor Data Engineers and other team members, fostering technical excellence and professional growth
• Guide teams through complex technical challenges and architectural decision-making
• Conduct technical design reviews and ensure adherence to architectural standards
• Establish coding standards, quality assurance processes, and engineering best practices
• Lead technical training programs and knowledge-sharing initiatives
• Drive continuous improvement in team processes, tools, and methodologies
• Participate in technical hiring processes and team capability building
  
  

Data Governance & Compliance

• Establish data classification systems, access control policies, and encryption strategies
• Implement automated data quality frameworks, lineage tracking, and metadata management
• Ensure regulatory compliance across data workflows (GDPR, SOX, industry-specific regulations)
• Design privacy-preserving techniques, data anonymization, and secure data sharing mechanisms
  
  

Strategic Collaboration & Stakeholder Management

• Partner with business stakeholders to translate strategic objectives into technical solutions
• Lead cross-functional initiatives spanning multiple engineering teams and business units
• Present technical concepts and architectural decisions to executive leadership
• Drive alignment between technical implementations and business outcomes
  
  

• Technical Expertise
• GCP Platform Mastery: 8+ years of hands-on experience with Google Cloud Platform, including deep expertise in BigQuery (advanced SQL, scripting, optimization, ML integration), Cloud Dataflow, Cloud Composer, Cloud Storage, Pub/Sub, Dataproc, and Vertex AI
• Programming Excellence: Expert-level Python/Java programming, proficiency in Python/Scala for Spark development
• Advanced Data Technologies: Deep expertise in Apache Beam, Apache Spark, Airflow, Kafka, and distributed computing architectures
• Infrastructure: Extensive experience with Terraform, CI/CD pipelines, and cloud infrastructure management
• Database & Data Modeling: Advanced knowledge of relational databases (PostgreSQL, MySQL) and NoSQL systems (BigTable, Firestore, MongoDB); expertise in data modeling, normalization, and performance optimization
• System Design: Proven ability to architect complex, distributed systems with considerations for scalability, reliability, security, and cost-effectiveness
• Professional Experience & Leadership
• Bachelor's degree in Computer Science, Engineering, or related technical field (Master's degree preferred)
• 8+ years of data engineering experience with 6+ years specifically on Google Cloud Platform
• Proven track record of leading end-to-end delivery of complex, enterprise-scale data platform initiatives
• Experience designing and implementing data governance, compliance, and security frameworks
• Strong architectural thinking with ability to make sound technical decisions and trade-offs
• Excellent communication skills with ability to present technical concepts to both technical and non-technical audiences, including executive leadershi
• Proven ability to translate business requirements into scalable technical architectures and solutions
• Experience managing cross-functional projects and building strong stakeholder relationships
  
  

• Google Cloud Professional Data Engineer and/or Cloud Architect certifications
• Experience with AI/ML technologies, MLOps practices, and machine learning pipeline development on GCP
• Knowledge of emerging AI technologies including Agentic AI frameworks, LLM integration, and Model Context Protocol (MCP)
• Experience with feature stores, model serving infrastructure, and AI/ML observability
• Understanding of data science workflows, statistical analysis, and advanced analytics
• Experience with BI and visualization tools (Looker, Tableau, Power BI)
• Contributions to open-source data engineering projects or technical publications
• Experience with multi-cloud or hybrid cloud architectures
• Knowledge of data mesh, data fabric, or other modern data architecture patterns
  
  

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.

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