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Easy Apply
Design and build secure data pipelines, lead data architecture, collaborate across teams, ensure data quality, and mentor other engineers.
Cybercrime is rising, reaching record highs in 2024. 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 secure 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 know we couldn’t take on this challenge without our incredible team. We 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. We are guided by our core values and our vision of a world without wire fraud. We offer a dynamic work environment where you can contribute to meaningful impact and be part of a team dedicated to enhancing security and fighting fraud.
We’re seeking an exceptional Staff Data Engineer to help us take our data platform to the next level. This is a high-impact role where you’ll architect and build scalable data infrastructure, empower data-driven decision-making, and help shape the future of fraud prevention. We’re scaling fast, and you’ll have the chance to shape the future of our data platform.
You will collaborate with data scientists, engineers, and business stakeholders to ensure high-quality, actionable data insights to enable business outcomes.
What You Will Do
- Design and build robust, scalable, secure data pipelines and infrastructure to support analytics, product intelligence, and machine learning.
- Lead data architecture decisions, ensuring high performance, reliability, and maintainability across our platform.
- Collaborate cross-functionally with product, engineering, and business teams to deliver data solutions that drive strategic insights and operational excellence.
- Champion data quality and governance, implementing best practices for data validation, lineage, and observability.
- Mentor and guide other data engineers, fostering a culture of technical excellence and continuous learning.
What We’re Looking For
- Proven experience as a staff-level data engineer in a fast-paced, product-driven environment. Engineering experience of 8+ years.
- Experience in leading teams of other engineers to build a long-term technical vision and plans to achieve it.
- Deep expertise in cloud data platforms (e.g., Snowflake, BigQuery, Redshift) and orchestration tools (e.g., Airflow, dbt).Strong programming skills in Python or Scala, and proficiency with SQL.
- Experience with real-time data processing (e.g., Kafka, Spark Streaming) and data modeling for analytics and ML.
- A growth mindset, strong ownership, and a passion for solving complex problems that matter.
Preferred Experience
- 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.
What We Offer
- Flexible vacation
- 12 company-paid holidays
- 10 paid sick days
- No work on your birthday
- Health, dental, and vision Insurance (including a $0 option)
- 401(k) with matching, and no waiting period
- Equity
- Life insurance
- Generous parental paid leave
- Wellness reimbursement of $300/year
- Remote worker reimbursement of $300/year
- Professional development reimbursement
- Competitive pay
- An award-winning culture
Change doesn't happen overnight, and the same goes for us here at CertifID. We PROGRESS collectively and individually as we grow, abiding by our core values. Protect the Customer, Raise the Bar, Operate with Urgency, Grow with Grit, Ride the Wave, Enthusiasm Spreads, Stay Connected, Send It.
Top Skills
Airflow
BigQuery
Dbt
Kafka
Python
Redshift
Scala
Snowflake
Spark Streaming
SQL
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