Analytics Engineer

Hightouch•New York, NY

7d•$170,000 - $220,000•Remote

About The Position

At Hightouch, the data team wears a lot of hats. We build the internal systems and data models that keep every part of the business moving quickly and reliably. We act as strategic advisors — using data to surface weaknesses and help the company continuously improve. Additionally, we engage directly with our largest customers to support high-impact data engineering initiatives. As an Analytics Engineer, you'll be primarily focused on owning our internal data models and serving as a trusted advisor to business leaders across Sales, Marketing and Finance. The ideal candidate is someone who can build rock-solid data systems and work with business leaders to continuously extract insights to guide the business. If you're looking for a role where your work has broad, visible impact across the entire company — this is it.

Requirements

Expert-level SQL skills and deep, hands-on experience with cloud data warehouses.
Hands-on experience building complex data models with dbt.
Experience with Omni Analytics or Looker.
Comfortable and confident engaging with business leaders and customers — you can walk into any room and earn credibility fast.
Curious about what problems the business has and how your work can add value
A strategic mindset — you proactively identify what matters, separate high-impact from low-impact work, and act accordingly.
High ownership mentality — you're someone who wants more responsibility, not less.
Thinks like a business analyst, executes like a software engineer.
Actively integrating AI into your day-to-day workflows — you've done the experimenting and you're learning where it adds real leverage.

Nice To Haves

Experience supporting multiple areas of a business simultaneously (Sales, Marketing, Finance, etc.).
Experience being on a data team at a startup.

Responsibilities

Design and maintain the internal data models and systems that power decision-making across Sales, Marketing, Finance — built to be reliable, scalable, and accessible to non-technical users.
Act as a strategic advisor to business leaders, proactively using data to identify areas of weakness and opportunity across the company.
Troubleshoot complex data issues, investigate discrepancies, and guide internal teams toward better upstream data practices.
Communicate findings and recommendations clearly to both technical and non-technical audiences.
Contribute to documentation, standards, and playbooks that make the analytics function more effective and scalable over time.
Measure and communicate the business impact of your work — revenue growth, efficiency gains, better decisions.