Head of Data

The Role

As One Pass scales rapidly, the demand for data-driven insights is growing. Data is central to product development, decision-making, and competitive advantage. This role involves building a data capability from the ground up, transforming data from a reporting function into a strategic product.

This is a unique opportunity for someone who thrives in a startup environment, enjoys creating scalable systems, processes, and teams, and has significant ownership over the evolution of the data function. The role requires balancing long-term strategy with hands-on execution, from defining a data vision and operating model to making critical architecture and design decisions.

The ideal candidate will oversee the Data organization, including data engineering, analytics, reporting, and data science. This is a people leadership role with direct management responsibility for the team, while also serving as a technical leader responsible for guiding the overall data strategy and platform evolution.

Reporting directly to the Head of Engineering, you will join a key member of the engineering leadership team. You will inherit a high-performing team of nine across data engineering, analytics, and data science, ensuring immediate and highly visible impact.

While people leadership is a core part of the role, this is not a purely managerial position. You will work closely with the Staff Data Engineer on technical leadership, contributing to key architectural decisions while staying hands-on with technology, partnering with engineers, and solving complex data problems.

You will play a pivotal role in defining the data platform, driving data quality and governance, and enabling the business to leverage data more effectively across every function. Most importantly, you will transform data into a strategic product capability that differentiates One Pass in the market.

Key Responsibilities

• Lead the transformation of data into a strategic product capability, identifying opportunities to leverage data as a competitive advantage and accelerate growth.

• Define and drive the company’s data vision, strategy, and roadmap, ensuring the data platform and capabilities scale alongside the business.

• Build, lead, and develop a high-performing data organization spanning data engineering, analytics, and data science, fostering a culture of accountability, collaboration, innovation, and continuous improvement.

• Partner closely with cross-functional leaders and stakeholders to translate company objectives into scalable data solutions, platforms, and insights that drive decision-making.

• Shape the technical direction of the data platform in partnership with the Staff Data Engineer, contributing to key architectural decisions while remaining hands-on in the design and implementation of critical systems and solutions. Establish engineering standards, best practices, and design patterns across the data ecosystem, while mentoring team members.

• Drive the evolution of data engineering practices, including data modeling, data quality, governance, security, observability, and validation frameworks to ensure trusted and reliable data at scale.

• Lead the design, implementation, and operation of cloud-based data infrastructure and services on AWS, balancing scalability, performance, reliability, and cost efficiency.

• Identify and prioritize investments in data platforms, tooling, and processes that enable faster product development, deeper customer insights, and increased organizational leverage.

• Serve as a key member of the engineering leadership team, influencing company-wide technology strategy and shaping how data powers future products, decisions, and growth initiatives.

About You

You are a strong technical leader who can leverage both technical and leadership skills, with a proven ability to solve complex engineering problems, focusing on system design, performance, and scalability. You thrive in ambiguity, creating clarity and balancing tradeoffs between short-term value and long-term architectural integrity. You enjoy mentoring engineers and scaling your impact by elevating the people and teams around you.

You thrive in a small, fast-moving company environment, comfortable wearing multiple hats and moving fluidly between strategic thinking and hands-on technical execution. Ideally, you have experience turning data into a product or business differentiator, not just internal reporting or BI.

Required Qualifications

• 7+ years of experience in data engineering, software engineering, data platforms, or related technical disciplines, with a track record of building and scaling data capabilities in high-growth environments.

• 3+ years of people management experience, including hiring, performance management, coaching, and career development of engineers, analysts, data scientists, or other technical professionals.

• Experience defining data architecture, platform strategy, and engineering standards for modern data ecosystems.

• Strong proficiency with SQL and deep understanding of relational database design, optimization, and performance tuning.

• Strong software engineering fundamentals and hands-on experience developing production systems with Python and other modern programming languages.

• Expertise with modern cloud data platforms and warehouse technologies such as Snowflake, Amazon Redshift, Databricks, or similar solutions.

• Experience designing, building, and operating scalable batch and real-time or near real-time data processing pipelines.

• Experience using GitHub or similar source control platforms in collaborative, distributed engineering teams.

• Excellent communication and stakeholder management skills, with the ability to translate business goals into technical strategies and influence decision-making across the organization.

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience building data products or data-driven features that serve as a competitive differentiator or revenue driver, beyond internal reporting/BI.

• Deep knowledge and hands-on experience with AWS tools such as Redshift, S3, MSK, Glue, SageMaker, Bedrock.

• Experience with Kafka, dbt, data orchestration tools (e.g., Airflow, Dagster).

• Experience working with both batch and near-real-time data processing pipelines.

• Solid experience designing and implementing scalable distributed systems.