{"id":778256,"url":"https://alion.io/job/nelo-senior-data-engineer","title":"Senior Data Engineer","company":{"id":62836,"name":"Nelo","domain":"nelo.mx","url":"https://alion.io/company/nelo","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Mexico City, Mexico","New York, United States"],"countries":["MX","US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":100000,"max":140000,"currency":"MXN","period":"month","gross":null,"usd_annual":90204},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Feature Store","optional":false},{"name":"Google BigQuery","optional":false},{"name":"IAM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Presto","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-08T16:13:06Z","employer_posted_date":"2026-09-08","last_verified_at":"2026-10-22T10:41:56Z","board_verified":true,"closed_at":null,"days_open":43,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":43},"description":"Location: Mexico City | New York City - in office\nAbout the Company\nNelo is a leading fintech in Mexico reimagining credit to expand consumer buying power. Founded in 2019 by former Uber international growth team leads Kyle Miller and Stephen Hebson, Nelo offers credit cards, BNPL loans, bill payments, and its own marketplace - all under one app - designed from first principles for a mobile-first, real-time payments world.\nWith $100M in annual revenue, $1B in annualized GMV, and $140M+ raised in equity and debt, Nelo is one of the most capital-efficient consumer fintech companies in Latin America. The company is profitable - positive operating profit in both 2024 and 2025. It runs lean and technical: 60 employees, 8 engineers, with AI driving underwriting, collections, and operations.\nHQ: Mexico City, Mexico; commercial and people operations in New York City\n\nFounded: 2019\n\nTeam size: 60 FTEs\n\nOpen roles: 10+\n\nWebsite: nelo.mx\n\nStage: Post-Series A; $100M credit facility (Victory Park Capital, 2022); profitable\n\nBenefits: 401k, open PTO, medical, dental, vision, STD, LTD, fertility\n\nCompany values:\nBe your best selves: ambition, hard work, intellectual curiosity\n\nEveryone is an owner: all employees receive equity including customer support; 10-year option expiration; equity refreshers\n\nCustomer first: product decisions grounded in customer benefit\n\nOpen and honest communication: quarterly financials and board presentations shared company-wide; low tolerance for bureaucracy or gossip\n\nMove fast, learn fast: hundreds of experiments run monthly; rigorous experimentation culture\n\nAbout the role\nWe are looking for a Senior Data Engineer to help design, build, and operate the core data platform that powers analytics, machine learning, and business decision-making at Nelo. This is a hands-on, high-impact role for an experienced engineer who enjoys working across the full data lifecycle, from ingestion and transformation to reliability, scalability, and ML enablement.\nYou will partner closely with Analytics, Product, Engineering, Marketing, Risk, and Machine Learning teams to ensure our data infrastructure is robust, scalable, and easy to build on as Nelo continues to grow.\nWhat you’ll do\nOwn and evolve the data platform: Design, build, and maintain scalable, reliable data pipelines and datasets that power analytics, reporting, and machine learning use cases across the company.\n\nBuild and maintain ETL/ELT pipelines: Develop production-grade pipelines that ingest data from transactional systems, third-party providers, and event streams into our data warehouse and feature store.\n\nEnable analytics and business teams: Partner with Data Analytics and stakeholders to ensure data is well-modeled, documented, and accessible for self-service analysis.\n\nSupport machine learning workflows: Build and maintain feature pipelines and feature stores that support model training, validation, and online/offline inference.\n\nEnsure data quality and reliability: Implement data quality checks, monitoring, alerting, and SLAs to ensure trust in our data products.\n\nImprove developer experience: Build tooling, abstractions, and CI/CD pipelines that make it easier and safer to develop, test, and deploy data pipelines.\n\nCollaborate cross-functionally: Work closely with Software Engineers, ML Engineers, and Product Managers to align data models and pipelines with product and business needs.\n\nScale for growth: Continuously improve performance, cost efficiency, and scalability of our data infrastructure as data volume and use cases expand.\n\nRole requirements\nAt least 5 years of experience in data engineering, software engineering, or backend engineering roles with significant ownership of production data systems.\nTechnical Skills\nStrong proficiency in Python for building data pipelines and infrastructure.\n\nAdvanced SQL skills and deep experience with data modeling for analytics and ML use cases.\n\nHands-on experience building ETL/ELT pipelines using tools or frameworks such as Airflow, AWS Glue, dbt, or similar orchestration systems.\n\nExperience working with cloud data warehouses and query engines such as Athena/Presto, Redshift, BigQuery, or Snowflake.\n\nFamiliarity with big data or distributed processing frameworks such as Spark (or equivalent).\n\nExperience designing and maintaining CI/CD pipelines for data workflows.\n\nExposure to feature stores, ML data pipelines, or close collaboration with ML Engineering teams is a strong plus.\n\nExperience with AWS (S3, IAM, Lambda, Glue, EMR, etc.) or similar cloud ecosystems.\n\nEngineering Mindset\nStrong understanding of data reliability, observability, and best practices for production systems.\n\nAbility to write clean, maintainable, and well-tested code.\n\nCollaboration & Communication\nProven ability to work cross-functionally with Analytics, ML, and Product teams.\n\nStrong communication skills to explain technical concepts to non-engineers and align on trade-offs.\n\nWhy you’ll succeed:\nYou enjoy owning systems end-to-end and making them better over time.\n\nYou balance speed, correctness, and long-term maintainability.\n\nYou’re excited about enabling others (analysts, scientists, and engineers) to move faster with high-quality data.\n\nYou’re comfortable operating in a fast-moving startup environment with evolving requirements.\n\nLocation:\nThis role is based in-office in Mexico City or NYC\nCompensation and Benefits:\nVery competitive salary and equity\n\n100% medical, dental & vision insurance coverage for you\n\nUnlimited PTO\n\n401(k) for US-based employees\n\nExtended maternity and paternity leave\n\nRelocation 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