Director of Data Engineering

Founded in 1986, OnTrac has evolved into the leading provider of same-day and next-day delivery services in the U.S. for premier e-commerce and product-supply businesses, including five of the largest retailers in the U.S.

Location

Remote - This position may be performed remotely in states where the company is authorized to employ individuals.

Pay

The expected starting base pay range for this position is $180,000 - $225,000, with full potential base salary range over a successful candidate’s tenure in the position of $180,000 - $270,000. Actual compensation will be determined based on experience, skills, internal equity, and other job-related factors. This position may also be eligible for bonus, commission, or other incentive compensation in accordance with the terms of the applicable plan of up to a 25% Bonus Target.

Benefits

• Medical, dental, and vision insurance
• Life and short- and long-term disability coverage
• 401(k) retirement savings plan with company match
• Flex vacation in states other than CA, CO, IL, MA, MT, and NE, with accruals up to 96 hours for first year of employment with tenure-based increases up to 160 hours
• Two (2) floating holidays per year
• Paid sick leave*
• Six (6) paid company holidays
• Two (2) weeks paid pregnancy disability leave, four (4) weeks paid parental bonding leave
• Additional wellness and employee assistance programs

*Washington state employees are eligible for up to 56 hours of paid sick leave annually.

Responsibilities

• Set the strategy and operating model for enterprise data engineering, including pipelines, platforms, tooling, standards, and the long-term migration to scalable data solutions.
• Oversee the design, development, performance, reliability, and uptime of ETL/ELT pipelines that extract, cleanse, enrich, and prepare data from core systems and non-system sources.
• Lead the development of governed, documented, and AI-ready data assets that support trusted analytics, certified reporting, self-service BI, and business decision-making.
• Partner with IT, business leaders, BI teams, analysts, and data stewards to define requirements, align metric definitions, strengthen governance, and ensure data products have clear business context.
• Establish and enforce data engineering standards, documentation practices, quality controls, and lifecycle processes that reduce duplication, improve consistency, and protect enterprise data integrity.
• Manage departmental budgets, staffing plans, priorities, and resource allocation to support high-value data initiatives and the efficient use of specialized talent.
• Build, lead, and develop a high-performing data engineering team, overseeing hiring, coaching, performance management, corrective action, and talent development.

Requirements

• 12+ years of relevant experience, including management experience, with a Bachelor’s degree or equivalent
• Deep knowledge of data engineering practices, including ETL/ELT pipelines, extraction layers, data cleansing, enrichment, performance optimization, and platform scalability
• Strong understanding of modern data architecture, including landing zones, cloud-based data platforms, analytics layers, reporting layers, data warehouses, data lakes, and AI-ready data assets
• Demonstrated ability to partner with IT, Operations, Commercial, Finance, corporate teams, BI engineers, analysts, and data stewards to align priorities and resolve data-quality or metric-definition issues
• Familiarity with GCP/BigQuery, OneLook, Power BI, and core operational/source systems such as FasTrac, OTM, Oracle, Salesforce, Dayforce, EPC, INVDB, YMS, SLOF, and SLEF
• Proficiency in SQL and Python, with the ability to guide the development of scalable data pipelines, analytics layers, reporting-ready datasets, and self-service BI models
• Familiarity with modern data engineering and analytics engineering practices, including Git-based development, CI/CD, documentation standards, dbt or similar transformation frameworks, Databricks or equivalent data processing platforms, and governed data lifecycle management
• Ability to travel up to 25%

Skills

• Strong governance mindset, establishing standards, documentation, controls, and repeatable processes that create a single source of truth and reduce inconsistent or conflicting metrics
• Strong financial and operational acumen to manage budgets, prioritize enterprise data initiatives, and allocate specialized talent to the highest-value work
• Ability to communicate complex technical and data concepts clearly to senior leaders, business stakeholders, and technical teams while maintaining appropriate confidentiality
• Ability to translate business requirements into governed, trusted, and well-documented data products that support analytics, BI, executive reporting, and operational decision-making
• Ability to translate business segment strategy into functional plans, lead effective execution, and contribute to enterprise-wide methodologies, best practices, and performance criteria for initiatives and talent