Head of Data Engineering

Experience and Skills

• 5+ years of experience designing and operating production data pipelines at scale, ideally within fintech or lending environments
• B2 English level or higher
• Demonstrated ability to produce a technical diagnostic and roadmap within the first weeks of a role and present it credibly to executive stakeholders
• Proven experience implementing medallion architecture with explicit schema contracts and lineage between layers
• Strong proficiency in Google Cloud (BigQuery) and Azure (Data Factory, ADLS)
• Track record of hiring and leading data engineering teams of 2 to 5 engineers, including standing up intake processes
• Production-level Python and strong SQL fluency, including BigQuery-specific optimization patterns like partitioning, clustering, and cost control
• Comfortable operating in a hands-on capacity alongside the team

Skills

• Data Engineering
• Python
• SQL
• Google Cloud
• BigQuery
• Azure
• Azure Data Factory
• ADLS
• Medallion Architecture
• Data Governance

Projects

As the Head of Data Engineering, you will build the data engineering function from the ground up in a high-growth fintech environment. Operating as a peer to the Head of Engineering and Chief Data Scientist, you will own all data pipelines, establish robust governance, and implement a medallion architecture across BigQuery and Azure. Your work will directly unblock critical modeling, underwriting, collections, and AI agent workflows. In this role, you will transition from hands-on execution to strategic leadership, delivering a comprehensive data diagnostic and roadmap within your first 30 days. You will establish cross-functional data contracts, evaluate cloud consolidation strategies, and hire a small team of engineers to scale the platform. This is a unique opportunity to shape the data culture and architecture of a transaction-heavy financial platform.

Key Responsibilities

• Lead the data engineering function build-out from zero, owning all pipelines and establishing freshness monitoring across Azure, GCP, and third-party integrations.
• Implement a medallion architecture consisting of bronze, silver, and gold layers to support feature stores and agent-ready data planes.
• Build a comprehensive data catalog and dictionary with canonical join keys and a full applicant data map.
• Deliver an architectural diagnostic and sequenced build roadmap within the first 30 days to executive stakeholders.
• Stand up intake and request-management processes for cross-functional stakeholders including Underwriting, Collections, and Product.
• Implement audit trails, identity governance, and cost monitoring across BigQuery and Azure platforms.
• Evaluate and drive the cloud consolidation strategy, proposing and executing the transition path toward Azure and Databricks.
• Hire, mentor, and lead the data engineering team as the platform scales.

Benefits

We provide the opportunity to participate in impactful and technically rigorous industrial data projects that drive innovation and professional growth. Our work environment emphasizes technical excellence, collaboration, and continuous innovation.

Niuro supports a 100% remote work model, allowing flexibility in work location globally. We invest in career development through ongoing training programs and leadership opportunities, ensuring continuous growth and success.

Upon successful completion of the initial contract, there is potential for long-term collaboration and stable, full-time employment, reflecting our long-term commitment to our team members.

Joining Niuro means becoming part of a global community dedicated to technological excellence and benefiting from a strong administrative support infrastructure that enables you to focus on impactful work without distraction.

Nice to Have

• Databricks
• Unity Catalog
• Apache Airflow
• Dagster
• GitHub Actions