Senior Data Engineer

Cybrid

$145K — $185K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of hands-on data engineering experience.
  • Experience with financial services data, specifically crypto or blockchain integrations.
  • Proficiency in SQL, PostgreSQL, and modern data pipeline frameworks (e.g., Airflow, dbt).
  • Expert in designing and scaling data warehouses and real-time streaming architectures.
  • Strong cloud platform experience (AWS, GCP, or Azure).
  • Familiarity with data modeling best practices in finance.
  • Understanding of data quality and governance frameworks for sensitive financial data.
  • Ability to utilize AI as a collaborator in data engineering tasks.

Responsibilities

  • Define and implement the data engineering strategy for Cybrid.
  • Build and maintain scalable ETL/ELT pipelines for data integration.
  • Develop a unified financial data platform and warehouse for analytics and reporting.
  • Implement real-time data processing pipelines for compliance and business intelligence.
  • Ensure compliance with data quality and governance practices.
  • Collaborate with departments to design AI-augmented workflows.
  • Build infrastructure for safely deploying AI on financial data.

Benefits

  • Opportunity to define and architect a cutting-edge data platform.
  • Collaborative environment working with diverse teams across the organization.
  • Focus on solving complex technical challenges related to financial data.
  • Direct involvement in shaping the future of global payments with AI integration.
  • Transparent and thorough interview process ensuring a fit for both employer and candidate.
Full Job Description
The Opportunity

We're expanding rapidly and looking for a Senior Data Engineer to define and build the data foundation that powers Cybrid's next chapter. This isn't a maintenance role, it's an opportunity to architect a financial data platform, set the standards for governance and quality, and make AI a first-class collaborator in how we make decisions. This is a chance to build cutting-edge infrastructure, solve complex technical challenges, and shape the future of global payments using the evolving integration of data with AI.

As Cybrid's dedicated data engineer, you'll own the data platform end-to-end: pipelines, warehouse, governance, and the AI-augmented workflows it empowers. You'll work directly with Sales, Finance, Compliance, Risk, and Engineering to turn clean, trusted data into a source for our AI agents to make informed decisions, accurate financial modeling, robust risk assessments, and reliable accounting.

What You'll Do
  • Define and implement Cybrid's data engineering strategy, setting up scalable architecture, governance, and technical standards.
  • Build and maintain robust ETL/ELT pipelines integrating data from microservices and external systems.
  • Develop a financial data platform and warehouse to unify transaction data for analytics and reporting.
  • Implement real-time, event-driven data processing pipelines to power compliance, operations, and agentic business intelligence.
  • Ensure regulatory compliance with strong data quality, governance, lineage, and security practices.
  • Partner with Sales, Finance, Risk, and Compliance to design AI-augmented workflows utilizing the data platform.
  • Build the infrastructure that makes AI safe and useful on financial data: retrieval layers, vector stores, semantic data catalogs, and human-in-the-loop review patterns.
  • Own and evolve Cybrid's BI and self-serve analytics layer: build the semantic models, dashboards, and access patterns that let all departments pull trusted data without going through engineering.


What You Bring
Required Skills & Experience:
  • 7+ years of hands-on data engineering experience.
  • Prior experience with financial services data, crypto, or blockchain integrations.
  • Expertise in SQL, PostgreSQL, and modern data pipeline frameworks (Airflow, Temporal, Prefect, dbt, etc.).
  • Proven experience designing and scaling data warehouses and real-time streaming architectures for change data capture (CDC).
  • Strong background in cloud-based data platforms (AWS, GCP, or Azure).
  • Knowledge of data modelling best practices in finance.
  • Knowledge of data quality, governance, and compliance frameworks for sensitive financial data.
  • Comfort using AI as a daily collaborator in your own work (code generation, query authoring, schema design, documentation) and an interest in scaling that practice across a team.
Nice to Have:
  • Prior experience in fintech or regulated industries.
  • Familiarity with modern data stack tools (dbt, Fivetran, Sigma, Looker, Tableau).
  • Familiarity with dlt for designing managed batch data pipelines.
  • Experience with Kafka for real-time data pipelines and change data capture upserts.
  • Exposure to machine learning pipelines, MLOps, or AI-assisted data workflows.
  • Practical experience integrating AI/LLM workflows into data platforms - RAG over warehouses, semantic data catalogs, agent-driven analytics, or AI-assisted data quality.
  • Strong knowledge of data security, privacy, and regulatory compliance (e.g., GDPR, PII).
  • Experience building AI agents that operate against financial systems (reconciliation, classification, anomaly detection) with a human-in-the-loop pattern.


About The Role

This role backfills an existing position. We have a preference for candidates based in Toronto or Ottawa, though we remain open to strong candidates in other locations in Canada. Cybrid's team uses automated tools and artificial intelligence throughout our recruiting process, including for note-taking during interviews and to support the review of take-home exercises.

The base salary range for this role is: Canada: CAD $145,000 - $185,000. Compensation will be based on your experience, skills, and the unique strengths you bring to the team. We take a thoughtful approach to levelling and internal equity when determining offers.
The Process

At Cybrid, our interview process is designed to be transparent, efficient, and thorough, moving from an initial HR alignment call through a hiring manager deep-dive and cross-functional stakeholder reviews to ensure we find the perfect balance of technical expertise and culture fit.

These are the steps in our hiring process:
  1. Pre-Screen Interview with a member of our Talent team (Virtual)
  2. Hiring Manager Interview (Virtual)
  3. Technical Interview (Virtual)
  4. Culture Interview (Virtual)
  5. Founder Interview/Final Interview (On-site in Toronto or Ottawa)

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