Lead Data Engineer

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

📋 Description

• Oversee, mentor, and nurture the data engineering team through regular one-on-one meetings and defined objectives.

• Establish benchmarks for code evaluations, testing protocols, documentation standards, and data on-call procedures.

• Coordinate the team's activities in collaboration with Engineering, Finance, and Product departments.

• Contribute to the team's development as it expands, including recruitment efforts.

• Take full responsibility for Trolley's Databricks lakehouse, managing ingestion, modeling, quality assurance, and cost control.

• Construct and maintain data pipelines sourced from the production platform, Salesforce, NetSuite, and other third-party systems.

• Ensure internal reporting in Sigma is precise, efficient, and user-friendly.

• Enhance the observability and recoverability of pipelines.

• Manage data processes for month-end closures, revenue assessments, and vendor cost reconciliations.

• Assist with audits and year-end financial reconciliations.

• Develop and enhance customer-facing data products, such as data connectors and embedded reporting features.

• Engage in data initiatives focusing on fraud detection and risk assessment.

• Establish data foundations for secure AI tools and agents.

• Leverage AI to accelerate the building, testing, and documentation of data pipelines.

• Identify and demonstrate opportunities where data and AI can enhance product and team operations.

• Integrate Jira and GitHub data into the warehouse to evaluate engineering performance.

• Implement data management and privacy protocols, collaborating with InfoSec and Compliance on access, retention, and audit requirements.

⛳️ Requirements

• Over 7 years of experience in data engineering, with accountability for a production data platform.

• Proven experience in leading engineers: managing, mentoring, or supervising a small team on a daily basis.

• Extensive knowledge of Databricks or a similar lakehouse, along with proficiency in SQL and Python.

• Experience in constructing dependable pipelines from operational databases and SaaS platforms.

• Familiarity with supporting finance or accounting operations through data solutions.

• Practical application of AI tools in your engineering practice, with a clear understanding of the advantages and limitations of AI.

• Comfortable being the most senior data professional in the organization, with significant autonomy.

• Formal experience in people management, with a desire to develop a team over time.

• Background in fintech, payments, or other regulated sectors.

• Experience with customer-facing data products, embedded analytics, or data sharing.

• Skills in building context layers, retrieval systems, or data pipelines for AI agents.

• Practical knowledge of data governance and privacy, including PII management, access controls, and GDPR compliance.

🏝️ Benefits

• Competitive salary.

• ESOP Program: Significant equity and ownership that aligns your success with the company's success.

• Comprehensive healthcare benefits starting from Day 1.

• 4 weeks of paid vacation each year, plus public holidays, with an additional vacation day for each year of service.

• Ability to work remotely for 30 days from any location.

• Gym membership reimbursement.

• Half-day Fridays off during the summer months.

• Company-provided Apple MacBook and related equipment.

• Join a remarkable team of diverse individuals united by a common mission.