Senior Data Engineer at Zip

Job description

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. Interesting problems you'll solve 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. What you'll bring to the team 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. What you’ll get in return Zip is a place where you’ll get out what you put in. The newness of our sector means we need to move at pace and embrace change, and our promise to you when you join the team is that you’ll feel empowered and trusted to make big things happen quickly. We want you to feel welcome and as though you have the support to be yourself, and care for yourself at work. Because it’s important to us that you make the most of the opportunities you’ll get to grow your skills and your career, and be surrounded by smart, friendly people and leaders that have your back. We think these are just some of the best things about being a Zipster. We will also offer you: Flexible working culture and incentive programs Unlimited PTO, generous paid parental leave and 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 The Pay Range for this position: $134,000 - $175,000 USD based on the industry benchmark for position, function, level and Zip's compensation strategies. However, actual base salary will depend on varying circumstances and individualized factors, such as job-related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include other elements, including a bonus and/or equity awards, in addition to a full range of medical, financial, and/or other benefits. Be a part of a team that reflects the diversity of our customers We pride ourselves on being a workplace that provides equal opportunities to people of all ages, cultural backgrounds, sexual orientations, gender identities, abilities, veteran status, and everything else that makes you unique. Equally, we’re committed to ensuring our recruitment processes are accessible and inclusive. Please let us know If there are any adjustments that need to be made to ensure you have a fair and equitable experience. And finally…get to know us Zip is a global ‘Buy Now, Pay Later’ company that gives our millions of customers simpler and fairer ways to pay. We are proud to be a global business built around our US and ANZ core markets working with merchant partners including Amazon, Best Buy, eBay and Uber. United by our mission, purpose and values - Customer First, Own It, Stronger Together & Change The Game - we are the next generation of payments, helping people across the globe to fearlessly take control of their financial future. We are Zip, and we are just getting started. Before you apply, give Zip a try -> rebrand.ly/check-zip-out Zip participates in the federal government’s E-Verify program

Requirements

Must-haves

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.
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.
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.
We value engineers who take ownership, remain hands-on, challenge existing approaches, and enjoy making the broader engineering team more effective.
Interesting problems you'll solve
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.
What you'll bring to the team
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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlpythonaimachine learningci/cdazureawsgcp

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

401k

Pto

Parental Leave

Wellness