Lead Data Engineer

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

📋 Description

• Take charge of the dbt project architecture, which encompasses model structure, naming conventions, testing standards, CI/CD pipelines, and documentation frameworks to maintain uniformity across all engineering efforts.

• Oversee the dataset delivery backlog in collaboration with onshore stakeholders, including phase scoping, validating the availability of source data, and sequencing builds to maximize business value.

• Ensure code quality governance by reviewing all Silver and Gold models before UAT, confirming that no production deployment takes place without lead approval.

• Manage the comprehensive dataset handover process from Build to Run, which includes test sign-off, data catalog documentation, observability setup, and operational runbooks.

• Organize and prioritize tasks across Build and Run workstreams that operate concurrently, ensuring alignment and efficient delivery.

• Engage in standups (async as needed) and lead sprint demonstrations every two weeks.

• In the Run steady state operations, be responsible for DataHub SLA performance, oversee the onboarding of new datasets, and serve as the ultimate escalation point for production support issues.

• Ensure DataHub SLA performance, maintaining pipeline uptime and data freshness commitments across all production Gold datasets.

• Manage the intake of new datasets from onshore teams, scoping requests and deciding whether they necessitate a new build phase or can be integrated into the Run team.

• Act as the primary escalation contact for onshore stakeholders and the final escalation point for critical incidents that the data operations team cannot resolve.

⛳️ Requirements

• Over 7 years of data engineering experience, with at least 2 years in a team lead or principal engineer position.

• Advanced knowledge of Snowflake: including warehouse management, RBAC, dynamic data masking, Snowflake Tasks, performance tuning, and query optimization.

• Proficient in dbt Cloud (advanced level): including incremental models, snapshots, macros, packages, Semantic Layer / MetricFlow, and CI/CD using GitHub Actions.

• Intermediate Python skills: focusing on Snowpark, pipeline scripting, and data quality automation.

• Expert in data modeling: including dimensional modeling, medallion architecture (Bronze / Silver / Gold), and retail data models (orders, inventory, customers).

• Advanced Git skills: including branching strategies, PR workflows, and managing shared dbt projects among multiple engineers.

• Intermediate Azure Data Factory skills: including pipeline monitoring and troubleshooting; capable of engaging IT confidently regarding pipeline issues (builds owned by IT).

• Preferred retail domain knowledge: familiarity with order management, inventory planning, and DTC data structures.

• Experience with AI & Automation Tools: hands-on use of tools such as GitHub Copilot, Cursor, Claude (or similar LLMs), Snowflake Cortex AI_COMPLETE, Elementary, and data observability platforms for AI-assisted development, SQL debugging, anomaly detection, alert classification, incident reporting, and workflow automation.

🏝️ Benefits

• Competitive salary and comprehensive benefits package.

• Opportunities for professional development and career advancement.

• Flexible working hours and remote work options.

• Collaborative and innovative work environment.