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Hunt St

We help Aussie companies find top 3% remote talent in the Philippines & Nepal for a single finder's fee.

Lead Data Engineer

Data EngineerData EngineerContractRemoteSeniorTeam 1-10H1B No SponsorCompany SiteLinkedIn

Location

Philippines

Posted

17 days ago

Salary

$4K - $5K / month

Seniority

Senior

7 yrs expEnglishAzureCloudPythonSQL

Job Description

Lead Data Engineer

Hunt St

• Own the dbt project architecture, including model structure, naming conventions, testing standards, CI/CD pipelines, and documentation frameworks to ensure consistency across all engineering work. • Manage the dataset delivery backlog with onshore stakeholders, including phase scoping, validation of source data availability, and sequencing of builds to maximise business value. • Govern code quality by reviewing all Silver and Gold models prior to UAT, ensuring no production deployment occurs without lead approval. • Own the end-to-end dataset handover process from Build to Run, including test sign-off, data catalogue documentation, observability configuration, and operational runbooks. • Coordinate and prioritise work across Build and Run workstreams operating in parallel, ensuring alignment and delivery efficiency. • Participate in standups (async where required) and lead sprint demonstrations on a fortnightly basis. • In Run steady state operations, own DataHub SLA performance, oversee new dataset onboarding, and act as the final escalation point for production support issues. • Own DataHub SLA performance, ensuring pipeline uptime and data freshness commitments are met across all production Gold datasets. • Manage new dataset intake from onshore teams, scoping requests and determining whether they require a new build phase or can be absorbed into the Run team. • Act as the primary escalation point for onshore stakeholders and the final offshore escalation for critical incidents that cannot be resolved by the data operations team.

Job Requirements

  • 7+ years data engineering experience (including 2+ years in a team lead or principal engineer role)
  • Snowflake (advanced): warehouse management, RBAC, dynamic data masking, Snowflake Tasks, performance tuning, and query optimisation
  • dbt Cloud (advanced): incremental models, snapshots, macros, packages, Semantic Layer / MetricFlow, CI/CD using GitHub Actions
  • Python (intermediate): Snowpark, pipeline scripting, and data quality automation
  • Data modelling (expert): dimensional modelling, medallion architecture (Bronze / Silver / Gold), and retail data models (orders, inventory, customers)
  • Git (advanced): branching strategies, PR workflows, and managing shared dbt projects across multiple engineers
  • Azure Data Factory (intermediate): pipeline monitoring and troubleshooting; ability to engage IT credibly on pipeline issues (build owned by IT)
  • Retail domain knowledge (preferred): familiarity with order management, inventory planning, and DTC data structures
  • AI & Automation Tools: Hands-on experience with 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.

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