Lead Data Solutions Developer

Commerce • Austin, TX

2d • $102,000 - $172,000 • Hybrid

About The Position

Welcome to the Agentic Commerce Era At Commerce, our mission is to empower businesses to innovate, grow, and thrive with our open, AI-driven commerce ecosystem. As the parent company of BigCommerce, Feedonomics, and Makeswift, we connect the tools and systems that power growth, enabling businesses to unlock the full potential of their data, deliver seamless and personalized experiences across every channel, and adapt swiftly to an ever-changing market. Simply said, we help businesses confidently solve complex commerce challenges so they can build smarter, adapt faster, and grow on their own terms. If you want to be part of a team of bold builders, sharp thinkers, and technical trailblazers, working together to shape the future of commerce, this is the place for you. At Commerce, we’re transforming how merchants harness data to scale their businesses and innovate online. As a Lead Data Engineer and Modeler, you will shape the foundational architecture that powers both our customer-facing analytics products and our internal decision-making systems. You’ll be at the forefront of building scalable, secure, and high-performance data infrastructure—enabling predictive insights, AI-driven tools, and analytics at enterprise scale. This role is a unique opportunity to influence the future of data at Commerce. You will collaborate across product, engineering, and data teams to design and optimize data platforms, ensuring they are built for both agility and long-term growth. Beyond infrastructure, you’ll drive data modeling best practices that translate business and product requirements into intuitive, reliable, and reusable structures. If you’re passionate about clean architecture, high-quality data systems, and enabling intelligence at scale, this role will give you the chance to lead Commerce into its next generation of data innovation.

Requirements

• 7+ years in data engineering, modeling, or analytics platforms, ideally within SaaS or product analytics environments
• Proven ability to design systems that support both real-time and batch workloads at scale
• Strong foundation in dimensional and normalized modeling, warehouse design, and ETL/ELT pipelines
• Exposure and interest in Data Architecture
• Hands-on experience with cloud warehouses (BigQuery, Snowflake), orchestration frameworks (Airflow, dbt, Spark, Flink), and BI tools (Looker, Tableau, Power BI)
• Skilled in SQL, Python, Bash, and Git-based CI/CD for data infrastructure
• Strong ability to partner with engineers, analysts, and product leaders to align architecture with business goals
• Skilled at simplifying complex systems and communicating technical solutions to diverse stakeholders
• Experience embedding data integrity, privacy, and compliance standards (GDPR, SOC) into large-scale platforms
• A passion for clean, scalable architecture and enabling intelligence through data

Nice To Haves

• Familiarity with event streaming platforms (Kafka, Kinesis), GraphQL, NoSQL databases, and cloud platforms (AWS, GCP).
• Exposure to embedded analytics, data APIs, and machine learning pipelines

Responsibilities

• Build a scalable, unified data lake and mart across clouds (GCP and AWS) and across different types of data storage in collaboration with the Enterprise Architect, Principal Data Architect and Product Engineering teams
• Partner with product, engineering, and data science to ensure the data architecture aligns with product goals and technical realities
• Select, implement, and manage the modern data stack—covering ingestion, transformation, storage, orchestration and access controls
• Drive performance, reliability, and cost-optimization of analytics systems at scale
• Adhere to existing technical patterns and standards for warehouse design, ETL/ELT pipelines, and data access APIs
• Work closely with the Product Managers to convert roadmap objectives into architectural blueprints
• Incorporate new data sources and translate business and analytics needs into technical requirements for data infrastructure
• Guide software development teams in adhering to data patterns and data quality best practices
• Champion data integrity, privacy, and security—embedding governance and observability into the data platform
• Implement scalable strategies for lineage tracking, cataloging, and metadata management across the entire organization
• Develop and maintain logical and physical data models to support customer-facing and internal analytics and business intelligence use cases
• Collaborate with product and engineering teams to align data models with evolving feature requirements and user workflows
• Establish modeling standards that ensure consistency, reusability, and performance across product domains, multi-tenant environments and different data storage types

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed