Staff Data Engineer

About the Role

Key Responsibilities

• Design and implement scalable, maintainable, and secure batch & streaming data pipelines and architectures that support enterprise-wide data needs
• Define standards for data modeling, data product design, and pipeline orchestration using modern tools and cloud-native technologies
• Collaborate with cross-functional stakeholders to translate business and analytical requirements into end-to-end data solutions
• Establish and enforce engineering best practices around code quality, testing, documentation, and deployment
• Contribute to the evolution of the data platform, ensuring systems are modular, interoperable, and resilient
• Lead technical design and code reviews, mentoring peers and raising the bar for engineering excellence
• Partner with data platform teams, analytics, and data science to deliver reusable data assets and shared infrastructure
• Identify and resolve architectural bottlenecks in the current data platform and propose performance improvements
• Drive initiatives that improve data quality, lineage, observability, and system reliability
• Act as a technical liaison between engineering, product, and analytics teams to ensure alignment on architecture and data strategy
• Provide technical leadership and guidance to other data engineers and contribute to the team's growth and maturity
• Help evaluate and onboard new technologies, frameworks, and practices to keep the data stack modern and efficient

Requirements

• 8+ years of experience in data engineering or a related field, focusing on building scalable data systems and platforms
• Strong expertise in modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure)
• Deep understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures
• Proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
• Experience owning complex technical systems end-to-end, from design through production
• Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences

Nice to Have

• Experience designing data platforms that support analytics, machine learning, and operational workload
• Familiarity with data governance, privacy, and compliance frameworks
• Background in customer-centric or product-driven environments (e.g., digital, eCommerce, SaaS)
• Experience with infrastructure-as-code and data platform observability (e.g., Terraform)

Qualifications

• Educational background is not explicitly specified, but extensive experience in data engineering is required

Benefits & Perks

• Health plans including options as low as $0 per paycheck, with programs for fertility, family planning, mental health, and fitness
• Generous paid time off (PTO & sick leave)
• Annual bonus and long-term incentive opportunities based on performance
• 401k with up to a 5% match
• Commuter benefits, pet insurance, and more
• Paid personal time off and 14 paid company holidays
• Medical, vision, dental, life, and disability insurance
• Potential for short-term or long-term incentive compensation, including cash bonuses and stock participation