Senior Data Engineer

This is a fully remote position, open to applicants in Philippines.

📋 Description

• Establish and manage client-specific data ingestion (ODBC, API, and file sources) into the warehouse through our ELT layer.

• Conduct thorough row-count and parity audits to validate raw data landings against the client’s source systems.

• Oversee comprehensive pipeline operations for multiple clients, directly addressing freshness issues, failure notifications, infrastructure expenses, and incidents.

• Develop and maintain isolated, three-tier dbt projects (staging → intermediate → marts) for each client engagement.

• Create robust fact and baseline models that accurately reflect a client’s source-of-truth numbers, generating reconciliation documentation for client approval.

• Uphold engineering standards by applying version-controlled, tested, peer-reviewed, and reproducible data practices using a structured local-to-CI workflow.

• Implement appropriately scaled engineering rigor for a startup environment, collaborating effectively with platform engineering without unnecessary enhancements.

• Engage directly with client operators, controllers, and analysts to extract essential domain logic and identify system patterns.

• Convert discovery discussions into precise metric definitions within the semantic layer and queryable business marts.

• Manage core business-rule tests and metric definitions (Cube.dev) that support executive dashboards and natural-language AI querying.

• Develop the quality framework utilizing automated dbt tests, anomaly detection, freshness monitoring, and PII awareness.

• Enhance and organize context-rich datasets with clean joins and clear definitions to enable correct reasoning by AI agents via the signal-mcp tool server.

• Ensure that all ongoing data operations capture structured traces that continuously contribute to our cross-client intelligence layers.

• Collaborate with and mentor other team members.

• Perform additional duties as required by the role.

⛳️ Requirements

• Over 7 years of experience in data engineering or analytics engineering.

• Experience in at least 2 of the following industries: Sales, Marketing, Finance & Finance-related, Media.

• Extensive hands-on ownership of cloud data warehouses, with a strong emphasis on query optimization, cost strategies, partitioning, clustering, and dataset architecture.

• In-depth knowledge of cloud data warehouse production, with a preference for Google BigQuery (Snowflake, Redshift, or equivalent acceptable).

• Expert-level proficiency with dbt Core, capable of building production projects from the ground up, managing layers, and establishing automated testing frameworks.

• Solid foundations in dimensional modeling, including Kimball methodologies, conformed dimensions, and canonical entity design.

• Proven ability to integrate and unify data from complex systems such as ERP (NetSuite, SAP), CRM (Salesforce, HubSpot), and HRIS (ADP).

• Confidently lead discovery workshops with non-technical executive stakeholders, controllers, and operational leaders.

• Track record of delivering reliable data outcomes in fast-paced startup or multi-client consulting environments.

• Experience working within effective teams using modern Git practices, including branching, code reviews, and keyless production deployments via CI.

• Driven to remain a hands-on builder in dbt and BigQuery on a daily basis, utilizing AI agent tools rather than transitioning into people management.

• Capable of easily adopting the analyst role, extracting business requirements, reverse-engineering domain models, and reconciling figures against source-of-truth reports.

• Strong written and verbal communication skills in English.

• Access to a fully functional and up-to-date computer to perform duties.

• Willingness to install next-generation endpoint protection on the computer.

• Current resident of the Philippines with the ability to work from there.

• Available to work within the US Pacific timezone (8am - 5pm PST, 12AM - 9AM Manila time) or during client hours as needed.

• Willing to undergo a 90-day probationary period upon initial hiring.

🏝️ Benefits

• Flexible scheduling options.

• Opportunities to maintain a balance between home life and work commitments.