Senior Data Engineer

Zip Co Limited

9d • $134,000 - $175,000 • Hybrid

About The Position

Build and own scalable data pipelines, modern cloud data platforms, and trusted data products that power critical business decisions across Zip. Apply strong SQL, Python, data modeling, and modern data engineering practices to solve complex problems at scale. Influence data architecture, improve platform reliability, and help shape the future of AI-ready data capabilities. Remote-first opportunity for US-based employees with the option to work in-person out of our Manhattan office. Start your adventure with Zip. We are seeking a collaborative, hands-on Senior Data Engineer to help build and evolve the data platform powering analytics, risk, finance, product, and critical business decisions across Zip. In this role, you'll design, build, and operate scalable data pipelines, trusted data models, and reusable data products across our modern cloud data platform. You'll take ownership of complex engineering challenges, improve data quality and reliability, and help ensure our data is accurate, accessible, governed, and ready to support both existing business needs and emerging AI-powered products. The ideal candidate brings strong Data Engineering fundamentals, experience owning production systems, and the technical judgment to design scalable solutions while balancing performance, reliability, and cost. Our Data Engineering team plays a critical role in enabling teams across Zip to make faster, more informed decisions. We work closely with Analytics, Risk, Product, Data Science, Machine Learning, and Engineering to solve complex problems, modernize our data capabilities, and build a trusted foundation for future innovation. We value engineers who take ownership, remain hands-on, challenge existing approaches, and enjoy making the broader engineering team more effective.

Requirements

• 5+ years of experience designing, building, and operating scalable data pipelines and enterprise data platforms in production environments.
• Advanced SQL and strong Python skills, with experience developing maintainable, tested, production-quality code.
• Hands-on experience with modern cloud data platforms such as Snowflake, Databricks, Microsoft Fabric, BigQuery, Redshift, or equivalent technologies.
• Strong data modeling fundamentals, including dimensional modeling, fact and dimension tables, slowly changing dimensions, and reusable analytical data models.
• Experience building ETL/ELT workflows using modern transformation frameworks such as dbt or equivalent technologies, along with orchestration tools such as Airflow, Dagster, or similar platforms.
• Experience with streaming, change data capture (CDC), or event-driven architectures using Kafka, Azure Event Hubs, Spark Structured Streaming, or comparable technologies.
• Strong understanding of modern data architecture patterns, including data warehouses, data lakes, lakehouses, and curated data products.
• Experience implementing data quality, automated testing, monitoring, observability, metadata, lineage, and governance practices.
• Hands-on experience with a major cloud provider, preferably Azure, although AWS and GCP experience are equally transferable.
• Strong software engineering fundamentals, including Git, code reviews, CI/CD, infrastructure automation, and production troubleshooting.
• Ability to independently make architecture decisions, evaluate technical tradeoffs, and improve platform scalability, performance, reliability, and cost efficiency.
• Experience collaborating across Engineering, Analytics, Product, Risk, Finance, and Data Science to translate complex business requirements into scalable technical solutions.
• Demonstrated ability to mentor engineers, establish reusable engineering standards, and contribute to the technical growth of a team.
• Familiarity with AI-enabled engineering tools and an interest in how modern data platforms support machine learning, intelligent applications, and AI-powered workflows.
• Clear alignment with Zip's core values: Customer First, Own It, Stronger Together, and Change the Game.

Responsibilities

• Design, build, and operate scalable batch, streaming, and event-driven data pipelines that integrate transactional systems, APIs, third-party providers, and enterprise data sources into our modern cloud data platform.
• Develop trusted, reusable data products and dimensional and semantic models that support analytics, risk, finance, product, and operational decision-making.
• Build and optimize ETL/ELT workflows using modern transformation and orchestration frameworks, improving data processing efficiency, scalability, and maintainability.
• Strengthen data quality, reliability, and observability through automated validation, reconciliation, freshness monitoring, anomaly detection, and proactive alerting.
• Design near-real-time data capabilities supporting transaction monitoring, fraud and risk signals, and operational intelligence.
• Improve platform performance and cost efficiency while establishing scalable architectural patterns across our warehouse and lakehouse environments.
• Build shared frameworks, self-service capabilities, and automated workflows that reduce repetitive engineering effort and accelerate delivery across teams.
• Implement strong engineering practices around CI/CD, automated testing, infrastructure as code, documentation, governance, and production ownership.
• Partner with Data Science and Machine Learning teams to develop reliable, AI-ready datasets and data pipelines that support emerging intelligent products and applications.
• Influence technical architecture, independently lead complex initiatives, mentor engineers, and help raise the engineering bar across Data Engineering.

Benefits

• Flexible working culture and incentive programs
• Unlimited PTO
• Generous paid parental leave
• Leading family support policies
• Company-sponsored 401k match
• Learning and wellness subscription stipend
• Union Square office with a casual dress code
• Employer-sponsored insurance for you and your dependents, with several 100% Zip-covered choices available

What This Job Offers

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