{"id":573787,"url":"https://alion.io/job/pavago-embedded-python-data-automation-engineer-5","title":"Embedded Python Data & Automation Engineer","company":{"id":1117,"name":"Pavago","domain":"pavago.co","url":"https://alion.io/company/pavago","size_band":null,"is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":194,"ghost_share":0,"stale_share":0.985,"repost_share":0,"time_to_fill_p50_days":34,"computed_at":"2026-10-26T05:57:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":{"label":"US time zones","utc_offset_min":-8,"utc_offset_max":-5},"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["AR","MX","CR"],"hiring_countries_total":3,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Git","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Slack","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-09T00:00:00Z","employer_posted_date":"2026-09-09","last_verified_at":"2026-10-26T04:07:04Z","board_verified":true,"closed_at":null,"days_open":47,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":47},"description":"Embedded Python Data & Automation Engineer - Data Pipelines, APIs & Automation | Remote\nPosition Type: Full-Time, Remote\nWorking Hours: Meaningful Overlap with U.S. Business Hours\nAbout the Role\nAt Pavago, one of our clients is hiring an experienced Embedded Python Data & Automation Engineer to take ownership of an existing Python environment, maintain production systems, improve data pipelines and automations, and develop practical internal tools and integrations.\nThis is a hands-on engineering role with an important initial focus on system transition and knowledge transfer. You’ll work closely with a departing programmer to understand the existing Python codebase, production workflows, integrations, dependencies, and automations before assuming ownership of the environment.\nAs the transition progresses, your focus will shift toward improving reliability, reducing technical debt, expanding automations, strengthening integrations, and building new internal tools based on business needs.\nIf you’re comfortable inheriting an existing codebase, troubleshooting production systems, and gradually making them more reliable and maintainable, this role is a strong fit.\nWhat You’ll Own\nSystem Transition & Technical Ownership\nShadow the departing programmer and absorb critical system knowledge\nTake ownership of the existing Python codebase\nUnderstand existing:\nApplications\nData pipelines\nScheduled automations\nAPIs and integrations\nDependencies\nDeployment workflows\nIdentify undocumented processes and system dependencies\nDocument critical knowledge throughout the handover process\nDevelop sufficient technical context to independently maintain and extend the environment\nEnsure a smooth transition with minimal disruption to production systems\nProduction Support & Maintenance\nTroubleshoot live production issues\nMaintain existing applications, scripts, and automated processes\nInvestigate failures and unexpected system behavior\nIdentify root causes and implement reliable fixes\nMonitor system stability and recurring technical issues\nRaise technical risks early\nPrioritize reliability when modifying existing production systems\nData Pipelines & Automation\nMaintain, debug, and improve production data pipelines\nMonitor scheduled automations and investigate failures\nImprove pipeline reliability and maintainability\nBuild new automations based on business requirements\nReduce repetitive manual processes through practical engineering solutions\nIdentify opportunities to improve existing automated workflows\nEnsure critical jobs and pipelines continue operating reliably\nAPIs & Integrations\nMaintain and extend existing APIs and third-party integrations\nWork with:\nAPIs\nAuthentication flows\nWebhooks\nThird-party services\nTroubleshoot integration and authentication issues\nMaintain reliable data exchange between systems\nExtend integrations as business requirements evolve\nDocument integration logic and dependencies\nTechnical Debt & System Reliability\nIdentify:\nFragile systems\nUndocumented dependencies\nTechnical risks\nMaintenance bottlenecks\nPrioritize technical debt based on operational impact\nRefactor and improve existing systems over time\nReduce unnecessary complexity where appropriate\nStrengthen system reliability without disrupting production\nFlag areas where existing architecture could create future operational risk\nDocumentation & Knowledge Management\nCreate and maintain:\nTechnical documentation\nWorkflow diagrams\nDependency maps\nOperating procedures\nDocument systems as you learn and modify them\nKeep technical documentation current as workflows evolve\nEnsure critical system knowledge is not dependent on a single individual\nMake troubleshooting and future development easier through clear documentation\nInternal Tooling & Development\nBuild practical automation tools and internal software based on business needs\nTranslate operational requirements into technical solutions\nScope new internal tools with client stakeholders\nExtend existing systems where appropriate\nBalance new development with production support and maintenance\nBuild solutions that improve operational efficiency and reduce manual work\nEngineering Practices\nUse Git and pull requests for version control and code review\nWrite and maintain automated tests where appropriate\nMaintain clear changelogs\nUse staged deployment workflows\nTest changes before releasing them into production\nFollow disciplined engineering practices while working within an existing environment\nRequirements\n3+ years of professional Python experience in a data-focused environment\nExperience building or maintaining production data pipelines and automations\nStrong experience with:\nAPIs\nThird-party integrations\nAuthentication\nWebhooks\nExperience working with an existing or legacy codebase\nWorking knowledge of SQL and relational databases\nFamiliarity with:\nGit\nPull requests\nAutomated testing\nDeployment workflows\nStrong troubleshooting and analytical skills\nStrong written English communication\nStrong technical documentation skills\nAbility to independently understand unfamiliar systems and code\nAbility to work with meaningful overlap with U.S. business hours\nNice to Have\nExperience taking ownership of systems previously maintained by another engineer\nExperience improving or modernizing legacy Python environments\nExperience developing internal business tools\nExperience with scheduled jobs and automation workflows\nStrong understanding of data pipeline reliability\nExperience with staged production deployments\nExperience working directly with business stakeholders to scope technical solutions\nTools & Technology\nPython | SQL | Relational Databases | APIs | Webhooks | Authentication | Git | Pull Requests | Automated Testing | Data Pipelines | Automation | Staged Deployments | Slack\nWhat Makes You a Strong Fit\nYou’ll likely thrive in this role if you:\nAre comfortable inheriting and understanding someone else’s code\nCan navigate an unfamiliar production environment methodically\nTroubleshoot technical problems rather than simply patching symptoms\nEnjoy building automations that eliminate repetitive work\nUnderstand how data pipelines, APIs, databases, and integrations work together\nDocument systems as you work\nIdentify fragile systems and technical risks before they become major problems\nCommunicate technical issues clearly and raise concerns early\nCan balance production maintenance with new development\nPrefer testing and staged releases over making unverified production changes\nTake ownership of systems from problem identification through resolution\nWhat a Typical Day Looks Like\nYour day may begin by checking overnight automations and reviewing any open production issues.\nYou’ll spend focused blocks working through the existing environment - reading Python code, running tests, tracing integrations, troubleshooting data pipelines, and filling documentation gaps.\nEarly in the engagement, a meaningful portion of your time will be spent in handover sessions with the departing programmer. As the transition matures, that time will increasingly shift toward new development, including building automations, improving pipeline reliability, and scoping internal tools with the client.\nYou’ll communicate primarily through Slack and participate in planning sessions and check-ins that align with U.S. business hours. You’ll be expected to raise flags early, document as you go, and push changes through staging rather than directly to production.\nIn short: you take ownership of an existing Python environment, keep critical systems running, and progressively improve the pipelines, automations, integrations, and internal tools the business depends on.\nKey Metrics for Success\nSmooth knowledge transfer from the existing programmer\nStable and reliable production systems\nSuccessful execution of scheduled automations\nReduced recurring pipeline and integration failures\nFaster identification and resolution of production issues\nImproved technical documentation coverage\nReduction in fragile or undocumented dependencies\nReliable APIs and third-party integrations\nConsistent use of testing and staged deployment practices\nSuccessful delivery of new automations and internal tools\nWhy This Role Stands Out\nDirect ownership of an established production Python environment\nHands-on work across Python, SQL, data pipelines, APIs, integrations, and automation\nMeaningful responsibility from the beginning through a structured technical handover\nBalance between production engineering and new development\nOpportunity to reduce technical debt and improve engineering practices\nDirect collaboration with client stakeholders\nFully remote working environment\nCareer growth opportunities into:\nSenior Python Engineer\nData Engineer\nAutomation Engineer\nTechnical Lead\nData & Automation Engineering Leadership\nInterview Process\nInitial Application\nSpark Hire One-Way Video Interview\nVideo Interview Screening\nClient Interview\nOffer Stage\nSpark Hire Video Interview - Required\nAs part of the application process, all candidates are required to complete a one-way video interview through Spark Hire.\nAfter completing the first step of your application, you’ll receive a Spark Hire invitation by email with instructions to record and submit your video responses.\nCompletion of the Spark Hire video is required to be considered for the next stage. Please check your inbox as well as your spam or junk folder for the invitation.\nApply Now\nIf you’re an experienced Python Engineer, Data Engineer, or Automation Engineer with hands-on experience maintaining production pipelines, APIs, integrations, and existing codebases, we’d love to hear from you.\nApply today and take ownership of the Python systems, data pipelines, automations, and integrations that support critical business operations.\n#PythonEngineer #PythonDeveloper #DataEngineer #AutomationEngineer #PythonAutomation #DataPipelines #SQL #APIs #Webhooks #Integrations #BackendEngineering #SoftwareEngineering #RemoteDeveloper #RemoteJobs #RemoteWork\n#LI-AG1","description_format":"text","description_chars":9994,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Upper-Intermediate (B2)","optional":false}]},"benefits":["Growth opportunities"],"hiring_locations":[{"name":"Argentina","iso":"AR","kind":"country"},{"name":"Mexico","iso":"MX","kind":"country"},{"name":"Costa Rica","iso":"CR","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Recruiting & Staffing","Employer of Record & PEO"],"lifecycle":[{"event":"open","at":"2026-09-09T15:21:58Z"}],"visa":[],"liveness":{"score":20,"band":"cold","label":"Long shot","p_open":1,"p_active":0.447,"p_room":0.44,"age_days":47,"expected_fill_days":34,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-26T05:57:25Z"},"pay":null,"html_url":"https://alion.io/job/pavago-embedded-python-data-automation-engineer-5","json_url":"https://alion.io/job/pavago-embedded-python-data-automation-engineer-5.json","meta":{"generated_at":"2026-10-26T07:08:33Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":9481,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-27T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1117},"rest":"https://alion.io/mcp/rest/get_company?id=1117"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpavago-embedded-python-data-automation-engineer-5"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpavago-embedded-python-data-automation-engineer-5"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpavago-embedded-python-data-automation-engineer-5"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/pavago-embedded-python-data-automation-engineer-5\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpavago-embedded-python-data-automation-engineer-5"}]}