Job Description:
- 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.
- Translate business understanding into architecture and design decisions.
- Drive the remediation and optimization of existing data assets.
- Ensure 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, including 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.
- Mentor engineers as the team grows.
Requirements:
- 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.
- Ability to translate business domain knowledge into architecture decisions.
- Demonstrated experience inheriting legacy data structures and remediating them end-to-end, including data cleanup, deduplication, and quality frameworks.
- Strong proficiency in Google Cloud (BigQuery).
- 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, including building rather than just directing.
- B2 English level or higher.