Description

 

• Design and Implement: Design, build, and maintain scalable, reliable, and efficient data pipelines (ETL/ELT) using modern data warehouse/lakehouse architectures, primarily on Google Cloud Platform (BigQuery, Cloud Composer, Dataflow, Dataform) and evolving toward a multi-cloud environment including Snowflake, Databricks, and Azure. 

• Data Modeling: Develop and enforce robust data models for optimal storage and analytical querying, tailored to business requirements. 

• Technology Evaluation: Research, evaluate, and recommend new data technologies, tools, and platforms to enhance the data stack and support CGO growth objectives. 

• Cost Management: Design cost-aware architectures and manage cloud resources (compute, storage, networking) with a focus on billing optimization, IAM permissions, quotas, and limits to ensure efficient and sustainable operations. 

• Pipeline Development: Write, test, and deploy production-grade batch data pipelines using Airflow (Cloud Composer), Dataform, and Apache Beam (Dataflow), ensuring high performance and data quality. 

• Data Governance: Implement data quality checks, monitoring, and lineage tools to ensure accuracy, consistency, and compliance across all data assets. 

• Cloud Infrastructure: Manage and optimize data-related cloud services (e.g., BigQuery, Snowflake, Azure, GCP) including computing, storage, and networking resources for cost-efficiency and performance. 

• API Integration: Build and maintain connectors to integrate data from various internal and external sources (e.g., Salesforce, SAP, CRM, marketing platforms, transactional databases). 

• Stakeholder Partnership: Work closely with Data Analysts, Data Scientists, and business stakeholders (Marketing, Sales, Product) to understand data requirements and deliver solutions that directly support growth strategies. 

• Documentation: Create and maintain clear, comprehensive documentation for data models, architecture, and ETL/ELT processes. 

• Experience: 5+ years of experience in a Data Engineering, Data Architect, or similar role. 

• Programming: Expert proficiency in SQL (especially BigQuery SQL) and strong programming skills in Python (or Scala/Java). 

• Data Warehousing: Extensive experience with cloud-based data warehouses (e.g., BigQuery, Snowflake, Databricks). Experience with Google Cloud Platform (BigQuery, Cloud Composer, Dataflow, Dataform) is highly valued. 

• Cloud Platform: Proven experience with at least one major cloud provider's data services (e.g., Azure, GCP). Multi-cloud experience or familiarity with Azure and Snowflake is a plus given our evolving architecture. 

• ETL/ELT Tools: Experience with modern orchestration tools (e.g., Airflow, Prefect, Dagster) and ETL/ELT frameworks (Dataform, dbt). 

• Big Data: Familiarity with Big Data technologies (e.g., Apache Beam, Spark, Hadoop) for batch processing is a plus. 

• Version Control: Proficiency with Git and CI/CD pipelines. 

• Enterprise Integrations: Experience building integrations with enterprise systems such as Salesforce, SAP, ERPs, and CRMs. 

• Certifications: Professional cloud certifications are highly valued (e.g., GCP Professional Data Engineer, GCP Professional Cloud Architect, Azure Solutions Architect Expert, or similar). 

• Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical audiences. 

• Problem-Solving: Strong analytical and critical-thinking skills with a demonstrated ability to solve complex data challenges. 

• Growth Mindset: A proactive, self-starter approach aligned with the fast-paced, results-driven environment of a Chief Growth Officer organization. 

• Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.