The Opportunity:
We are building a brand-new, state-of-the-art Google Cloud data infrastructure to ingest, process, and analyze vast quantities of real-time and historical motorsports data. This includes high-frequency timing data, vehicle telemetry, sensor readings, and more, from the most dynamic and demanding sporting environments in the world. This is a unique opportunity to shape the future of motorsports data analytics from the ground up, leveraging the power of Google Cloud to derive unprecedented insights.
Role Summary:
As a Cloud Data Engineer specializing in Google Cloud, you will be a foundational member of our new data team, responsible for designing, building, and maintaining robust and scalable data pipelines and infrastructure. You will be instrumental in transforming raw motorsports data into actionable intelligence, enabling AI/Machine Learning applications and dynamic dashboards for our customers and internal teams. This role requires significant self-initiative and the ability to drive projects from conception to completion in a remote-first, high-performance environment.
Key Responsibilities:
• Google Cloud Infrastructure Design & Implementation: Architect, develop, and deploy scalable and cost-effective data solutions on Google Cloud Platform (GCP). This includes selecting and configuring appropriate GCP services for data ingestion, storage, processing, and serving using Terraform.
• Data Pipeline Development: Design, build, and optimize robust ETL/ELT pipelines for ingesting high-volume, real-time streaming data (e.g., timing, telemetry, sensor data) from diverse motorsports sources into BigQuery and other GCP data stores via Cloud Functions and Pub/Sub.
• Data Modeling & Warehousing: Develop and maintain optimized data models within BigQuery and other analytical databases to support high-performance querying, reporting, and advanced analytics.
• Data Integration for AI/ML: Work closely with future AI/ML engineers and data scientists to ensure data is readily available, clean, and in the correct format for model training, inference, and deployment.
• Dashboard & Reporting Integration: Facilitate seamless data integration with business intelligence tools (e.g., Looker Studio, Grafana) to create insightful dashboards for internal and external stakeholders.
• Performance Optimization & Cost Management: Continuously monitor and optimize the performance and cost-efficiency of data pipelines and infrastructure on GCP.
• Data Governance & Security: Implement best practices for data quality, security, privacy, and compliance within the data platform.
• Troubleshooting & Support: Provide expert-level troubleshooting and support for the data infrastructure and pipelines.
• Documentation: Create comprehensive technical documentation for data architecture, pipelines, and processes.
• Innovation & Research: Stay current with emerging Google Cloud technologies, data engineering trends, and best practices, proactively identifying opportunities for improvement and innovation.
• Self-Initiative & Project Ownership: Take ownership of data projects, from initial requirements gathering to deployment and ongoing maintenance, demonstrating a high degree of autonomy and problem-solving skills.
Required Skills & Experience:
• Extensive Google Cloud Platform (GCP) Experience (3+ years): Proven hands-on experience designing, implementing, and managing data solutions on GCP.
• Google BigQuery Expertise: Deep proficiency in BigQuery for data warehousing, analytics, and complex SQL querying. Experience with BigQuery AI/ML is a plus.
• Data Pipeline Technologies: Strong experience with GCP data ingestion and processing services such as:
* Cloud Dataflow (Apache Beam): For scalable batch and streaming data processing.
* Cloud Pub/Sub: For real-time messaging and event ingestion.
* Cloud Storage: For scalable and durable data lake solutions.
• Database Proficiency: Experience with various database types, including relational databases (e.g., Cloud SQL) and NoSQL databases (e.g., AlloyDB, Cloud Firestore, Bigtable), understanding their best use cases.
• Programming Languages: Strong programming skills in Python (preferred) for data engineering tasks. Experience with C# or C++ is a bonus due to existing systems.
• SQL Mastery: Advanced SQL skills for data manipulation, analysis, and optimization.
• API Integration: Experience with integrating data from various APIs and external sources.
• Self-Starter & Autonomous: Demonstrated ability to work independently, prioritize tasks, and manage projects end-to-end with minimal supervision in a remote setting.
• Problem-Solving: Excellent analytical and problem-solving skills, with a keen eye for detail.
• Communication: Strong written and verbal communication skills in both English and Spanish.
• Adaptability: Ability to thrive in a fast-paced, evolving technological environment.
Desired Qualifications (Nice to Have):
• Experience with other GCP services like Vertex AI, Data Catalog, Cloud Composer (Airflow).
• Familiarity with containerization technologies (Docker, Kubernetes/GKE).
• Knowledge of CI/CD practices for data pipelines.
• Understanding of motorsports data types and analysis.
• Experience working with real-time analytics and low-latency data processing.
• Previous experience in a remote-first or highly distributed team.
