Lead Data Engineer

Experience and Skills

• 5+ years of experience designing and operating production data pipelines at scale, ideally within fintech or lending environments
• Proven ability to quickly understand a business domain and how its data is generated, and translate that into architecture decisions
• Demonstrated experience inheriting legacy data structures and remediating them end-to-end — data cleanup, deduplication, and quality frameworks
• Strong proficiency in Google Cloud (BigQuery) and working knowledge of Azure (Data Factory, ADLS)
• Production-level Python and strong SQL fluency, including BigQuery-specific optimization patterns like partitioning, clustering, and cost control
• Experience implementing medallion architecture with explicit schema contracts and lineage between layers
• Experience mentoring engineers or leading small teams is a plus
• Hands-on by default — you build, not just direct
• B2 English level or higher

Skills

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

Projects

This is an opportunity to own a fintech data platform end-to-end as a Lead Data Engineer. The role covers optimizing the customer database, building modern pipelines from SQL Server to BigQuery, and laying the architecture that powers underwriting, collections, and AI workflows. Real ownership from day one — understand the business first, then build the data foundation to scale it.

Key Responsibilities

• Own the end-to-end data platform: architecture, pipelines, quality, and governance.
• Develop a deep understanding of the business and how its data is generated, and translate that into architecture and design decisions.
• Drive the remediation and optimization of existing data assets, ensuring quality, consistency, and reliability across core datasets.
• Design, build, and operate reliable data pipelines between SQL Server, BigQuery, and third-party integrations.
• Define and implement the target data architecture, including layered modeling (medallion), data cataloging, and lineage.
• Establish governance practices across the platform — auditability, access, and cost efficiency across BigQuery and Azure.
• Partner with cross-functional stakeholders (Underwriting, Collections, Product) to align data capabilities with business needs.
• Shape the long-term cloud and data strategy, and mentor engineers as the team grows.

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