Sr. Data Engineer

High velocity, high intensity, high trust, high bar, high impact, and a will to win.

If those words resonate deeply with you, this could be your next career move. We're seeking someone who leads with humility, pursues audacious goals, and is motivated by meaningful impact on people and the world.

At FutureFit AI, our core mission is to help more people get to better jobs faster and cheaper, with a specific focus on those facing barriers to opportunity. Our work helps resolve the growing issue of economic inequality, ensuring that no one is left behind in the future of work. Our AI-powered platform brings efficiency and insight to workforce development, replacing outdated systems and unlocking human potential at scale.

Ready to make an impact? Apply today.

Important note: Data shows that men typically apply when meeting 3/10 requirements, while women often wait until it's 10/10. We encourage you to apply if you see a strong (not necessarily perfect) fit.

We’re seeking a Sr. Data Engineer to join our team. You will play a key role in evolving our core data platform which includes data pipelines, machine learning models, and various databases. Combine technical data expertise with strong business intuition to build a foundation of reliable data. Your expertise in data engineering will help us build strong, performant pipelines.

• Our data infrastructure: Building and maintaining the infrastructure that powers our data platform including pipeline orchestration, data warehousing, and machine learning

• Data solutions that drive the product: Develop and maintain data solutions alongside a team of data scientists that enable our product to function at scale and with quality

• Data governance and quality: Uphold best practices in data governance, ensuring accuracy, accessibility, and compliance across data systems

• Cross-platform data sourcing: Surface and integrate data from across the platform to address real business needs in product, engineering, and GTM.

• Evolving core data models: Continuously evolve our foundational models by identifying and incorporating new, high-value data sources.

30 days:

• Onboarding/Learning Stack/Product

• Learn who are customers are, what their problems are, and how we can leverage data to support them

• Gain an understanding of our core data entities and how they drive the product

• Contribute to our core data pipelines by adding of data quality and data enrichment layers

60 days:

• Work with data scientists to develop datasets and processes that streamline complex workflows

• Contribute to and own aspects of our data catalog by defining and maintaining metrics, dimensions, and lineage

• Support surrounding teams in getting value out of our platform’s data through regular reporting and analysis

90 days:

• Own and automate reporting workflows from data ingestion all the way to building out dashboards and tools

• Independently gather reporting and insights requirements from stakeholders

• Present findings to stakeholders and provide recommendations to drive us towards making data-driven decisions

• Proven ability to translate ambiguous business problems into clear, actionable insights

• Hands-on experience using SQL and Python for analysis in a professional setting

• Experience building and maintaining data pipelines, warehouses, and infrastructure

• Strong communication skills to convey technical insights to both technical and non-technical stakeholders

• Demonstrated ownership of analytics solutions, ensuring accuracy, reliability, and business alignment

• Familiarity with data visualization tools such as Looker, Power BI, or Tableau

• Familiarity with modeling structured and unstructured data, including NoSQL databases like MongoDB

• A sharp, kind, and open-minded approach, driven by both excellence and impact

• Hands-on experience with modern data tools like DBT and Airflow.

• Experience with SageMaker or an equivalent machine learning / data science platform

• Experience in the workforce development industry
  

• Languages: SQL, Python

• Data orchestration and transformation: Airflow, dbt

• Data storage and warehousing: PostgreSQL, Redshift, MongoDB (for unstructured data)

• Machine learning and experimentation: AWS SageMaker

• Visualization and reporting: Looker

• Infrastructure: AWS ecosystem (S3, Lambda, Glue, Redshift)

Your alma mater isn’t our focus. Your grit, hunger, and drive are. If you learn continuously, tackle challenges head-on, and know your strengths and gaps intimately—you’re our person.

This is a hybrid role open to candidates living in Toronto. Our office is conveniently located at 325 Front St West (a short walk from Union Station). The team comes in 1-2x a week, usually on Wednesdays. We'd love to see you too!

Although this role is remote, you may be expected to travel up to once per quarter.

The base salary range for this role is $150,000-$180,000. This range reflects the varying levels of expertise and responsibilities that will be determined through the interview process, based on applied experience and other criteria established by the hiring committee.

At FutureFit AI, our hiring process is designed to help you assess whether this role and our culture are the right fit based on your unique skills, mindset, and experiences. We move fast and work with intensity, so we want you to get a real sense of that from the start.

Each journey includes a mix of interviews and a performance challenge. For this role, that might look like:

1. Online Application

2. Initial Screen with Recruiting Partner

3. Interview with Hiring Manager

4. Performance Challenge

5. Final 1:1 Interviews

6. Final Decision

Generally, this entire process takes around 6 weeks, although the timing can vary due to specific candidate circumstances.

At FutureFit AI, we're not just building a company—we're transforming how talent and opportunity connect. Join our driven team united by a commitment to job seekers and the workforce ecosystems we serve.

• Team: 30-50 across US and Canada (hubs in NYC and Toronto)

• Customers: Workforce development agencies and intermediaries, government agencies, employers

• Industry: SaaS/AI technology

• Funding: Bootstrapped 0-1, then raised funding led by JP Morgan

• Structure: Growth, Customer Success, Product, Engineering, Data, People & Culture, Finance & Operations

• Be Curious

• Drive to Outcomes

• Raise the Bar

• Speed Matters

• Own It

• We Over Me

At FutureFit, we use artificial intelligence (AI) tools to make our hiring process more efficient, consistent, and equitable—never to replace human judgment. We use AI in the following ways:

• Screening support: AI may help us compare applications against the skills and experience required for a specific role. These skills are defined by the hiring team for each position. A human reviews each application, with the AI assessment as just one input.

• Interview support: In some interviews, we may use an AI notetaker to summarize the discussion so interviewers can focus on being present in the conversation.

• Insights, not decisions: AI provides data points to support our team’s evaluation but does not make or recommend final hiring decisions. Every hiring decision is made by people.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please contact us to request an accommodation.
© FutureFit AI All rights reserved, we are proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, gender identity, sexual orientation, age, disability, veteran status, or other applicable legally protected characteristics. We encourage people of different backgrounds, experiences, abilities, and perspectives to apply.