Data Engineer

Certifid•Austin, TX

1d•Hybrid

About The Position

Cybercrime is rising, reaching record highs. According to the FBI's IC3 report total losses exceeded $16 billion. With investment fraud and BEC scams at the forefront, the message is clear: the real estate sector remains a lucrative target for cybercriminals. At CertifID, we take this threat seriously and provide a platform that verifies the identities of parties involved in transactions, authenticates wire transfer instructions, and detects potential fraud attempts. Our technology is designed to mitigate risks and ensure that every transaction is conducted with confidence and peace of mind. We are guided by core values and a world without wire fraud. Our team is committed to enhancing security and fighting fraud- where your work drives real, meaningful impact. We know we couldn’t take on this challenge without our incredible team and have been recognized as one of the Best Startups to Work for in Austin, made the Inc. 5000 list, and won Best Culture by Purpose Jobs two years in a row. Our core values define who we are and how we work: Guard The Customer: We exist to protect people, their money and their trust. We start with their problem and build secure solutions worthy of the responsibility. Raise The Bar: Growth is something we choose every day. We push ourselves to learn, improve, and do our best work. Influence Outcomes: Leadership is how you show up. We take ownership, act with urgency, and follow through. Teamwork Wins: Great work is a team effort. We show up for each other, communicate openly, and get better together. About This Role We’re seeking a talented and driven Data Engineer to help us elevate our data platform. This is a high-impact role where you’ll contribute to the design and development of scalable data infrastructure, support data-driven decision-making, and play a key role in shaping the future of fraud prevention. You’ll work alongside experienced engineers and cross-functional teams in a fast-paced environment with plenty of growth opportunities.

Requirements

5+ years of experience in data engineering or analytics engineering, ideally supporting GTM or business functions in a fast-paced environment.
Proven ability to manage data integrations across platforms such as Salesforce, HubSpot, Amplitude, Sigma, Clay, and similar tools.
Expertise in Python with strong SQL skills and experience building with a modern data stack (BigQuery, dbt, Fivetran, Airflow).
Familiarity with credit or financial data and the regulatory considerations that come with handling sensitive information.
Hands-on experience with AWS or GCP, containerization (Docker, Kubernetes), and CI/CD pipelines.
Experience building and maintaining scalable data visualization solutions (Sigma, Looker, Tableau).
Strong communication and stakeholder management skills, with the ability to partner effectively with executives and non-technical teams.
A bias toward action, comfort working in ambiguity, and a strong sense of ownership — you find answers rather than wait for direction.

Nice To Haves

Experience in fintech, cybersecurity, or fraud prevention.
Familiarity with data privacy regulations (e.g., SOC 2, GDPR, CCPA).
Contributions to open-source data tools or communities.

Responsibilities

Design, implement, and maintain ETL/ELT pipelines that pull and merge data from multiple internal and external systems, ensuring clean, reliable, and scalable data flows across the organization.
Own the data warehouse architecture, including partitioning strategy, access controls, and security, in partnership with Security and Infrastructure teams to meet compliance and performance requirements.
Partner with data science, engineering, Revenue Operations, and executive stakeholders to define and track KPIs, translating complex requirements into reliable data solutions that drive strategic decisions.
Champion data quality and governance, ensuring insights are consistent, trustworthy, and well-documented across the organization.
Take full ownership of billing data infrastructure, including backend warehouse tables, data models, and ongoing maintenance.
Build dashboards and analytics that deliver actionable insights for executive leadership, GTM, product, and finance teams.
Share knowledge and support the growth of peers through code reviews, documentation, and informal mentorship.