Senior Data Engineer & Tech Lead - AI-Driven Platform

Mudflap; United States; Hybrid; USD 180,000 - 235,000; Full time

Benefits offered by this job

Commuter benefits

Lunches and snacks

Collaborative, high-growth environment

Job summary

Mudflap is rebuilding the data foundation for our rapidly growing fintech platform that powers the trucking industry. We seek a Staff Data Engineer, Tech Lead, to own architecture, governance, and scalability across a cloud data platform.

You'll partner with product, operations, finance, and risk to translate needs into robust data solutions, mentor engineers, and push the adoption of AI tooling while leading end-to-end projects.

Qualifications

• Bachelor's or Master's degree in Computer Science or related field.
• 8+ years of data engineering experience with 3+ years in senior or staff roles.
• Hands-on with AI-assisted and agentic engineering.
• Proven data ingestion frameworks (batch and streaming).
• Strong SQL and Python with cloud data platforms experience.

Responsibilities

• Act as the overall technical leader for data engineering and architecture.
• Lead cross-functional initiatives end to end from scoping to delivery.
• Drive organization-wide technical alignment with staff leadership.
• Own AI and agentic workflows in data engineering.
• Architect and scale ingestion frameworks for diverse data sources.
• Own ML deployment architecture in partnership with data science.
• Define data schemas, governance, and lifecycle management.
• Mentor engineers and promote code quality and design reviews.
• Drive adoption of modern tooling for orchestration and lineage.

Skills

SQL

Python

Leadership

Data modeling

Communication

Education

Bachelor's or Master's in Computer Science or related field

Tools

Snowflake

BigQuery

Databricks

Redshift

Job description

Mudflap is rebuilding the data foundation for our rapidly growing fintech platform that powers the trucking industry. We seek a Staff Data Engineer, Tech Lead, to own architecture, governance, and scalability across a cloud data platform.

You'll partner with product, operations, finance, and risk to translate needs into robust data solutions, mentor engineers, and push the adoption of AI tooling while leading end-to-end projects.