Coo Jobs

About The Position

Requirements

• 5+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 4+ years with orchestration tools (Cloud Composer/Airflow) and CI/CD (Cloud Build, Git‑based workflows) for data workloads
• 4+ Python and Spark for building data pipelines, libraries, and automation tooling
• 4+ years of advanced SQL and data modeling for analytics and warehousing; experience with ETL/ELT design patterns
• 4+ years’ experience with automated testing, data quality checks, and monitoring for pipelines and platform services
• 4+ years’ experience with logging/monitoring stacks (Cloud Logging, Cloud Monitoring, error reporting, metrics dashboards
• 3+ years of experience with core GCP data services: BigQuery, Dataflow/Apache Beam, Dataproc, Pub/Sub

Nice To Haves

• Bachelor’s degree in computer science, Engineering, or related field, or equivalent
• Experience with knowledge graphs and semantic search
• Excellent communication and presentation skills across technical audiences
• Advanced Data Modeling skills, including data modeling in tabular and MPP models, design, composite models, and performance optimization of large, complex datasets
• Strong SQL expertise and hands‑on experience with Starburst and/or Trino, including connector configuration, query optimization, and secure data federation across GCP data stores
• Collaborative mindset with a focus on partnering across business, finance, risk, and technology teams to deliver high‑quality, reconciled data, APIs, and reporting outcomes
• Experience in large financial services organizations (100k+ employees)
• Experience with Agile transformations and technology roadmaps
• Experience working with onshore and offshore teams

Responsibilities

• Lead the design and implementation of scalable, secure data platforms on Google Cloud using managed services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Composer)
• Build reusable frameworks and tooling (ingestion, transformation, quality, orchestration) that can be adopted by multiple product and domain teams
• Develop shared transformation libraries in Python/SQL/Beam (e.g., common SCD patterns, data quality checks, masking/tokenization routines)
• Provide orchestration capabilities via Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration
• Optimize cost, performance, and reliability of GCP data workloads (partitioning, clustering, storage classes, autoscaling strategies)
• Build opinionated data ingestion frameworks (e.g., config‑driven pipelines, connectors, schema handling, error handling) on top of Dataflow, Dataproc, or Composer
• Implement robust data modeling (dimensional, data vault, or canonical models) and semantic layers in BigQuery and related tools
• Enforce data quality, lineage, and observability using standardized metrics, validation rules, and monitoring dashboards
• Partner with domain data engineers, analytics, and ML teams to onboard use cases onto platform services and frameworks
• Document patterns, runbooks, and best practices, and provide enablement through workshops and code examples
• Contribute to platform roadmap, tool selection, and evaluation of new GCP services and open‑source components

Benefits

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement