Lead Data Engineer · Remote

Niuro; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Findjobit is seeking a Lead Data Engineer to own a fintech data platform end-to-end. You will optimize customer data stores, build modern pipelines from SQL Server to BigQuery, and lay the architecture powering underwriting, collections, and AI workflows. Real ownership from day one.

You will partner with underwriting, collections and product, mentor engineers, and shape the long-term cloud strategy while ensuring governance, quality, and cost efficiency across the stack.

Qualifications

• 5+ years designing and operating production data pipelines at scale.
• Experience with medallion architecture, data cataloging, and lineage.
• Strong SQL and Python with BigQuery optimization.
• B2 English level or higher and Spanish fluency required.

Responsibilities

• Own the end-to-end data platform architecture, pipelines, quality, and governance.
• Translate business needs into scalable data designs.
• Remediate and optimize existing data assets for quality and reliability.
• Design and operate pipelines between SQL Server, BigQuery, and third-party integrations.
• Define target data architecture with medallion modeling, lineage, and cataloging.
• Establish governance on cost, access, and auditability across platforms.
• Collaborate with underwriting, collections and product to align data capabilities.
• Mentor engineers and lead small teams; hands-on implementation.

Skills

Python

SQL

Data pipelines

Cloud platforms

Mentoring

Tools

BigQuery

Azure Data Factory

ADLS

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, 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.

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, 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

• Fluent Spanish is required: the team works in Spanish day to day.