Staff Data Engineer (Tech Lead)

• As a Staff Data Engineer, Tech Lead, you’ll play a mission-critical role in designing, scaling, and governing our modern, cloud-based data platform — and in leading the team and the projects that deliver it.
• Your expertise in data ingestion, data architecture, schema design, and governance will help shape how data flows across our systems and is leveraged by teams company-wide
• Act as the overall technical leader for the data engineering, owning architecture direction, setting standards, and making the design decisions that unblock the team
• Lead high-impact, cross-functional initiatives end to end — scoping the problem, sequencing the work, and driving it to delivery. Partner with manager on team and project management processes, from sprint planning to team processes
• Drive organization-wide technical alignment, representing data in staff engineering leadership forums and partnering with engineering leaders across the company on shared initiatives
• Serve as our thought leader on AI and agentic workflows in data engineering, and deepen the team’s AI transformation
• Architect and scale ingestion frameworks to bring diverse data sources (internal systems, third-party APIs, streaming events) into our platform in a reliable, high-throughput way
• Own and evolve the architecture for machine learning deployment in partnership with our data science teams, building the infrastructure and patterns that move models from prototypes to reliable, monitored production serving
• Define and enforce data schemas, and establish best practices for data modeling, schema evolution, and data lifecycle management, to ensure data integrity, discoverability, and interoperability across teams
• Own data governance strategy, including data quality, metadata management, lineage, and compliance with security and privacy requirements
• Design and optimize system-wide data architecture to support analytics, agentic, and operational use cases at scale
• Partner with product, engineering, analytics, compliance, and business functions (Operations, Finance, Risk, etc.) to align data architecture with business and regulatory needs
• Mentor other engineers, leading by example in code quality, architecture reviews, technical design discussions, and effective use of AI tooling
• Drive adoption of modern tooling for orchestration, lineage tracking, and cataloging to improve platform robustness and usability

Benefits

• A high bar for quality and commitment to self-improvement
• A team of talented individuals on a mission to change a $1 trillion industry for the better
• An open mind to new ideas and methodologies
• Opportunities and support for massive career growth
• A flexible, remote-first company- Experience building or owning machine learning deployment infrastructure — feature pipelines, model serving, and production monitoring — in partnership with data science teams
• Bachelor’s or Master’s degree in Computer Science (or related technical field)
• Proven expertise in data ingestion frameworks (batch and streaming)
• Hands-on experience with AI-assisted and agentic engineering, with a clear point of view on where agents create leverage in data work and where they don’t
• Experience with orchestration tools (Airflow, Dagster, Prefect) and metadata/catalog platforms (dbt, DataHub, Amundsen, or similar)
• Strong command of SQL and Python, with ability to design performant, reusable components
• Excellent communication and leadership skills, with a track record of mentoring engineers and influencing cross-functional stakeholders and senior leaders
• Deep experience with cloud-native data platforms (Snowflake, BigQuery, Databricks, or Redshift)
• 8+ years of data engineering experience, with at least 3+ years in senior or staff-level roles
• Ability to set long-term technical vision while driving execution on near-term deliverables
• Hands-on knowledge of data governance frameworks (quality checks, lineage, cataloging, security, compliance)
• Strong understanding of data warehouse methodologies, dimensional and normalized modeling, and distributed system design
• Track record as a tech lead, owning technical direction for a team or major platform area and delivering multi-quarter initiatives with several engineers and cross-functional partners