Data Engineer

Skills

About the Role

You will join a growing data platform team and take end-to-end ownership of designing, building, and scaling the foundational data infrastructure that powers analytics, machine learning, and business decision-making across the company. You will independently drive the design and delivery of reliable, secure, and cost-efficient data platforms, enabling data engineers, analysts, and data scientists to do their best work. You will lead technical efforts in close partnership with engineering, analytics, and security teams, improving platform reliability, performance, and developer experience for high-impact data workloads at scale. You will bring strong engineering judgment to ambiguous technical problems, drive architectural decisions, and actively contribute to growing the technical capability of the team.

Requirements

• 3+ years of experience with Apache Airflow or a comparable orchestration platform, including building and maintaining DAGs for production workloads
• 3+ years of experience developing in Python, writing readable, testable, and maintainable code in a data engineering context
• 3+ years of experience with Databricks or a comparable distributed data platform, including designing and delivering ETL/ELT pipelines using Delta Lake or similar technologies
• Demonstrated ability to design and own end-to-end data systems with a focus on scalability, reliability, and operational observability
• Solid experience working in cloud environments (AWS, Azure, or GCP), including cloud storage, IAM, and managed services
• Experience with infrastructure as code (Terraform preferred)
• Proficiency with Git-based workflows and CI/CD practices
• Strong engineering judgment when navigating ambiguous technical problems
• Experience mentoring junior engineers or leading technical initiatives within a data engineering team
• Familiarity with data quality, observability, or lineage tools (e.g., Monte Carlo, Datafold)
• Experience with dbt and a clear understanding of how transformation layers fit into a modern data stack
• Exposure to data governance, privacy, or compliance practices
• Experience supporting BI, analytics, or data science teams in a platform or infrastructure capacity

Responsibilities

• Own the design, development, and delivery of scalable data pipelines and platform components built on Databricks and Airflow from requirements through production
• Drive performance monitoring and optimization of data workflows, proactively identify bottlenecks, diagnose root causes, and implement improvements independently
• Lead design and code reviews, setting the bar for code quality, testability, and engineering standards
• Make independent technical decisions on pipeline architecture, data modeling, and tooling trade-offs
• Own operational excellence for production batch and near-real-time pipelines, build and maintain monitoring, alerting, and runbooks, and lead incident response and postmortems
• Build and maintain comprehensive documentation for pipelines, data models, and platform workflows
• Partner with analytics, data science, and engineering teams to drive adoption of platform capabilities, enforce data governance standards, and deliver against shared roadmap commitments
• Mentor junior engineers through pairing, code review feedback, and technical guidance

Benefits

• Health plans including programs for fertility and family planning, mental health support, and fitness benefits
• Generous paid time off (PTO & sick leave)
• Annual bonus and long-term incentive opportunities
• 401k with up to a 5% match
• Commuter benefits
• Pet insurance
• 14 paid company holidays