Data Engineer II

• Collaborate with stakeholders across the Finance team to understand business requirements and translate them into well-defined, actionable data sets for analysis and reporting.
• Design, develop, and maintain scalable data extraction and ELT pipelines in Google Cloud Platform (GCP) to process structured and unstructured data from diverse sources including databases, REST/SOAP APIs, and cloud storage systems.
• Leverage a suite of GCP services such as Big Query, Dataform, Cloud Run Functions, Workflows, Airflow, Pub/Sub, and Cloud Storage to build efficient, secure, and high-performing data workflows.
• Manage infrastructure as code using Terraform and maintain code and CI/CD pipelines in GitLab following branching, review, and deployment best practices.
• Build, test, and maintain AI agents and internal AI tooling to automate repetitive data engineering and finance workflows and improve productivity across the team.
• Continuously monitor and optimize data pipelines for performance, scalability, reliability, and cost-efficiency.
• Manage and monitor scheduled production jobs (Daily, Weekly, Bi-Weekly, and Monthly), ensuring timely and accurate data processing across all cycles during PST business hours.
• Provide production support during critical month-end data load windows (Day 1 to Day 5), ensuring data availability and resolving issues swiftly to meet business reporting deadlines.
• Maintain clear and thorough technical documentation and runbooks for data pipelines, workflows, integrations, and system architecture to support ongoing development and cross-functional collaboration.
• Support Looker dashboards and ML models that serve finance and business stakeholders.
• Identify opportunities for improvement in existing applications and workflows, recommending and implementing scalable solutions that enhance system functionality and user experience.
• Provide insights by collecting, analyzing, and summarizing data-related development and operational issues to support troubleshooting and continuous improvement.
• Manage multiple tasks and projects simultaneously, effectively prioritizing work across the full lifecycle of data engineering initiatives.
• Respond to and fulfill ad-hoc data requests from business stakeholders, delivering timely and accurate datasets or insights to support decision-making and operational needs.
Required Qualifications:
• Bachelor's and/or master’s degree in computer science, Computer Engineering, or a related technical discipline.
• 3–5 years of hands-on data engineering experience, with a strong understanding of the architectural differences between transactional systems and analytical data warehouses.
• Hands-on experience with Google Cloud Platform (GCP) services, including BigQuery, Dataform, Cloud Run Functions, Workflows, and Pub/Sub.
• Strong experience reading data from REST and SOAP APIs and building data applications using Python (JavaScript and Java a plus).
• Proven expertise in building, deploying, and maintaining data pipelines using tools such as Apache Airflow / Cloud Composer and Dataform.
• Experience managing infrastructure as code with Terraform.
• Proficiency with GitLab, CI/CD tools and methodologies.
• Experience designing and writing efficient ETL/ELT jobs to ingest and transform data into Google Cloud Storage and BigQuery, ensuring scalability, performance, and data integrity.
• Advanced SQL proficiency, with the ability to write, optimize, and manage complex queries in high-volume data environments.
• Strong skills in data visualization, with experience creating dashboards using Looker, Google Data Studio or similar BI tools; exposure to ML models is a plus.
• Experience building or working with AI agents / AI-powered automation tools to improve productivity is highly desirable.
• Experience supporting scheduled production jobs during critical finance month-end data load cycles, ensuring data accuracy, timeliness, and system reliability throughout the Day 1 to Day 5 close period.
• Availability to work in the PST time zone to support production jobs and ad-hoc requirements.
• Solid understanding of cloud architecture design principles, including performance and cost optimization.
• Exceptional attention to detail, with a commitment to delivering high-quality, reliable work.
• Self-starter with the ability to thrive in unstructured environments, manage ambiguity, and independently drive initiatives forward.
• GCP certifications (e.g., Professional Cloud Developer, Professional Cloud Database Engineer) are a strong plus.