{"id":3716590,"url":"https://alion.io/job/zip-co-senior-data-engineer-2","title":"Senior Data Engineer","company":{"id":685645,"name":"Zip Co","domain":"zipcolimited.com","url":"https://alion.io/company/zipcolimited","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":88,"open_postings":4,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":56,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":134000,"max":180000,"currency":"USD","period":"year","gross":null,"usd_annual":180000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Apache Iceberg","optional":true},{"name":"Delta Lake","optional":true},{"name":"Embeddings","optional":true},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-11-03T20:19:30Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T05:46:35Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Build and scale the modern data platform powering analytics, risk, finance, and critical business decisions across Zip.\n\nOwn end-to-end data pipelines, dimensional models, and trusted data products using modern cloud data technologies.\n\nDrive data platform reliability, performance, and engineering excellence while influencing architecture and mentoring other engineers.\n\nRemote-first opportunity for US-based employees, with the option to work in person from our Manhattan office.\n\nAbout the Role\nAs a Senior Data Engineer at Zip, you’ll build and operate the data foundation powering analytics, risk, finance, product, and critical business decisions across the organization.\nYou’ll own scalable pipelines, data models, and trusted data products across our modern warehouse and lakehouse, ensuring data is accurate, reliable, discoverable, and cost-efficient. You’ll partner across Analytics, Risk, Product, Data Science, ML, and Engineering to solve complex data challenges and increasingly enable AI-powered product.\nThis is a hands-on senior role where you’ll own meaningful parts of Zip’s data platform, influence architecture, and raise the engineering bar across the team.\nWhat You'll Do\nDesign, build, and operate scalable batch and streaming data pipelines that move data from transactional systems, event streams, APIs, third-party providers, and other sources into Zip’s warehouse and lakehouse.\nDevelop and maintain dimensional, semantic, and domain-oriented data models that support analytics, reporting, finance, risk, product, and operational use cases.\nBuild reliable ELT/ETL workflows using modern transformation and orchestration frameworks, with strong practices around testing, version control, deployment, and monitoring.\nOwn data quality end to end - including validation, freshness, anomaly detection, reconciliation, observability, and clear alerting when data does not behave as expected.\nBuild curated, reusable, and well-documented data products that downstream teams can consume without repeatedly rebuilding business logic.\nDesign and implement event-driven and near real-time data solutions for use cases such as transaction monitoring, risk and fraud signals and operational intelligence.\nImprove the scalability, performance, reliability, and cost efficiency of assigned data platform across compute, storage, and pipeline workloads; provide recommendations for broader platform changes.\nApply and contribute to engineering best practices for modular design, automated testing, CI/CD, observability, lineage, documentation, infrastructure as code, and operational ownership.\nSupport data governance, security, access controls, privacy, and compliance requirements appropriate to a regulated financial services environment.\nBuild self-service data capabilities, shared frameworks, and tooling that reduce ad-hoc requests and enable teams to move faster with trusted data.\nPartner with Data Science and Machine Learning teams to deliver reliable datasets and pipelines for model development, experimentation, and production workloads.\nHelp evolve Zip’s data foundation for emerging AI use cases through high-quality data products, strong metadata, and support for structured and unstructured data where appropriate.\nPartner with stakeholders to understand requirements, evaluate technical tradeoffs, and translate business problems into scalable data solutions.\nIndependently deliver and lead technical initiatives, contribute to architecture and design decisions, mentor engineers, and help raise the technical bar across Data Engineering.\nWhat You'll Bring\n5+ years of experience designing, building, and operating production data pipelines and data platforms at scale.\nAdvanced SQL and strong Python skills, with a track record of writing maintainable, tested, production-quality code.\nDeep experience with modern cloud data platforms such as Snowflake, Databricks, Microsoft Fabric, BigQuery, Redshift, or similar technologies.\nStrong data modeling fundamentals, including dimensional modeling, slowly changing dimensions, semantic layers, and designing data for analytical and operational consumption.\nHands-on experience with modern transformation frameworks such as dbt or equivalent technologies.\nExperience with workflow orchestration frameworks such as Airflow, Dagster etc.\nExperience designing and operating streaming or event-driven architectures using technologies such as Kafka, Azure Event Hubs, Spark Structured Streaming, or similar platforms.\nStrong understanding of modern data architecture patterns across data warehouses, data lakes, lakehouses, and reusable data products.\nExperience implementing data quality, testing, observability, metadata, lineage, and monitoring practices in production environments.\nHands-on experience with a major cloud platform - Azure preferred; AWS and GCP.\nStrong software engineering practices including Git-based workflows, code review, automated testing, CI/CD, infrastructure automation, monitoring, and operational ownership of what you build.\nUnderstanding of security, privacy, governance, and access-control considerations for enterprise data systems.\nA strong sense of ownership for data accuracy, consistency, reliability, and usability - including the judgment to recognize when the data simply doesn’t look right.\nProven ability to independently lead complex technical initiatives, mentor engineers, and communicate effectively with both technical and non-technical stakeholders.\nNice to Have\nExperience with modern lakehouse technologies and open table formats such as Apache Iceberg, Delta Lake, or similar technologies.\nExperience preparing data for machine learning workloads, including feature pipelines, training datasets, or serving layers.\nFamiliarity with how AI and LLM-powered applications consume enterprise data, including unstructured data, metadata enrichment, embeddings, semantic retrieval, or similar patterns.\nExperience implementing enterprise data contracts and data catalogs, lineage, metadata management, or data discovery capabilities.\nExperience with Infrastructure as Code and cloud-native deployment technologies.\nExperience working with regulatory, compliance, or audit-driven data requirements.\nExperience in fintech, payments, lending, risk, fraud, compliance, or other highly regulated environments.\nWhat Success Looks Like (First 6-9 Months)\nWithin your first 6-9 months, you’ll be a trusted technical leader delivering high-impact data initiatives that create measurable value across Zip. You’ll deliver complex projects end to end, improve the reliability and scalability of our data platform, and build reusable solutions that accelerate teams across the organization. You’ll raise the engineering bar through strong technical ownership, sound architecture, and solutions built to scale.\nWhat you will get in return\nZip 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.\nWe want you to feel welcome and supported to be yourself and care for yourself at work. You'll have opportunities to grow your skills and your career, surrounded by smart, friendly people and leaders who have your back.\nFlexible working culture and incentive programs\nUnlimited PTO, generous paid parental leave and leading family support policies\nCompany-sponsored 401k match\nLearning and wellness subscription stipend\nUnion Square office with a casual dress code\nEmployer-sponsored insurance for you and your dependents, with several 100% Zip-covered choices available\nThe annual base Pay Range for this position is $134,000 - $180,000. This range reflects our US national compensation (USN). Additional premium percentages may apply based on our tiered premium strategy.\nSubject 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.\nIf hired, employees will be in an 'at-will position' and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation or benefit program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.\nBe a part of a team that reflects the diversity of our customers\nWe 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.\nEqually, 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.\nAnd finally…get to know us\nZip Co Limited (ASX: ZIP) is a digital financial services company, offering innovative, people-centered products.\nOperating in two core markets - Australia and New Zealand (ANZ) and the US, Zip offers access to point-of-sale credit and digital payment services, connecting millions of customers with its global network of tens of thousands of merchants. We’re proud to be a values-led business and our values - Customer First, Own it, Stronger Together and Change the Game - guide us in everything we do.\nI acknowledge by clicking \"Submit Application\", that the information provided is true and correct. I also understand that any willful dishonesty may render for refusal of this application or immediate termination of employment. By providing your information, you acknowledge that you have read our Zip Applicant and Candidate Privacy Notice and authorize Zip to process your data subject to those terms. 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