{"id":3992422,"url":"https://alion.io/job/vertex-staff-data-engineer","title":"Staff Data Engineer","company":{"id":58884,"name":"Vertex","domain":"vertexinc.com","url":"https://alion.io/company/vertexinc","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":79,"open_postings":6,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-11-09T06:03:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Uruguay"],"countries":["UY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Amazon Aurora","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"ETL/ELT","optional":false},{"name":"IAM","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon ECS","optional":true},{"name":"Amazon EKS","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Bitbucket","optional":true},{"name":"CI/CD","optional":true},{"name":"dbt","optional":true},{"name":"Docker","optional":true},{"name":"Fastify","optional":true},{"name":"Gmail","optional":true},{"name":"GraphQL","optional":true},{"name":"Great Expectations","optional":true},{"name":"JavaScript","optional":true},{"name":"Jenkins","optional":true},{"name":"Kubernetes","optional":true},{"name":"Node JS","optional":true},{"name":"Notion","optional":true},{"name":"Pandas","optional":true},{"name":"Prisma","optional":true},{"name":"Slack","optional":true},{"name":"Terraform","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-11-09T23:56:52Z","employer_posted_date":"2026-11-09","last_verified_at":"2026-11-09T23:56:52Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Description:\nRemote - Argentina, Brazil | Hybrid - Montevideo, Uruguay\nLead the design and evolution of large-scale, mission-critical data systems powering a tax automation platform, owning the end-to-end flow from ingestion and validation to domain modeling, file generation, and regulatory submissions.\nDrive the design of complex, multi-tenant ETL/ELT and streaming pipeline topologies; establish standards for modularity, testing, data contracts, and reproducibility across teams.\nTackle performance and correctness challenges in Spark/PySpark and Python, reducing latency and costs while improving SLAs/SLOs through robust retry, idempotency, and back-pressure patterns.\nOwn production-grade data infrastructure on AWS, including EMR/EMR Serverless, RDS/Aurora, S3, Glue, and Iceberg/Delta; champion security, multi-AZ resilience, and cost governance.\nDefine the technical roadmap for platform scale, covering workload isolation, schema evolution, partitioning, compaction, and caching; introduce observability through data lineage, quality SLAs, and reliability metrics.\nMentor senior engineers, conduct deep design reviews, and partner with product managers and tax subject matter experts to translate ambiguous requirements into reliable, production-grade data products.\nRequired Qualifications\n8-10+ years in data engineering or adjacent fields, with a consistent track record of delivering and operating large-scale, business-critical data systems.\nExpert-level proficiency in Python and SQL, with strong Spark/PySpark skills and demonstrated performance tuning and cost optimization at scale.\nDeep experience designing ETL/ELT and streaming pipelines, large-scale orchestration with Airflow or equivalent, and data contract and testing frameworks.\nStrong data modeling skills across 3NF, star schema, wide tables, and domain modeling, with comfort in schema evolution and governance in multi-tenant environments.\nHands-on experience with AWS data services including S3, Glue, EMR, RDS/Aurora, IAM, and KMS, with production operations experience covering monitoring, alerting, on-call, and incident response.\nProven technical leadership in setting engineering standards, conducting architecture reviews, and driving cross-team initiatives.\nStrong bias for automation, reliability engineering, and measurable outcomes defined by SLIs and SLOs.\nPreferred Qualifications\nExperience with Iceberg or Delta lakehouse patterns, dbt, Great Expectations, OpenLineage, or comparable data quality and lineage tooling.\nExposure to Kafka, Kinesis, CDC patterns, and event-driven pipeline architectures.\nContainer and Kubernetes experience, with infrastructure-as-code using Terraform.\nBackground integrating data systems with Node.js backends or REST/GraphQL service layers.\nPractical experience applying LLMs or ML to data quality, extraction, or workflow automation use cases.\nEquivalent combination of education, training, and relevant professional experience accepted in lieu of a formal degree.\nTools We Use\nData: Python, Pandas, Spark, Airflow\nBackend: Node.js, TypeScript, Prisma, Fastify\nCloud Infrastructure: AWS (EMR, S3, SQS, RDS, ECS, EKS)\nAutomation and Infrastructure: Docker, Kubernetes, Terraform\nCI/CD: Jenkins, Bitbucket Pipelines\nProject Management: Atlassian Suite, Notion\nCommunication: Gmail, Slack\nCOMMENTS:\nThe above statements are intended to describe the general nature and level of work being performed by individuals in this position. Other functions may be assigned, and management retains the right to add or change the duties at any time.\nVertex Values: Together We Win\nWe're building a team of people who are passionate about making an impact for our customers and committed to how that impact is achieved. Our values define the behaviors, mindset, and culture that make Vertex a great place to grow and do meaningful work.\nPlay to Win or We Don't Play - If we choose to do something, we're choosing to do it because we plan to win. That mindset raises our bar on product quality, customer outcomes, and how we show up for one another.\nWork As a Team, Putting the Customer At the Core - Our customers are our true north. Whatever your role, ask: how will this help a customer succeed today? We earn trust through outcomes, not promises.\nAchieve Excellence With Integrity, Speed, and Agility - The market isn't slowing down. We'll move faster, adapt quickly, and never compromise on doing things the right way - for teammates, customers, and partners.\nInnovate Boldly With a Growth Mindset - Progress demands smart risk. We'll try new approaches, learn fast, and keep pushing the boundaries - especially where AI can remove friction and unlock value.\nCommunicate with Care, Candor and Transparency - Honest, constructive conversations make us better. Let's speak plainly about what's working and what isn't and help each other improve.\n Pay Transparency Statement:\nAnnual Salary Range: $2,021,800.00 - $2,695,700.00Pay Basis: Monthly\nThe expected base salary range for this role varies by location and is expressed in local currency. The posted range reflects the anticipated hiring range for successful candidates at the time of hire, based on relevant job-related skills, experience, geographic location, and business needs. Base pay offered to new hires may vary within the posted range depending on individual qualifications and market considerations.\nThe posted salary range reflects compensation at the time of hire. Employees may experience additional compensation growth over time through performance-based increases, expanded responsibilities, role progression, or internal career opportunities, in accordance with company policies and local practices.\nIn addition to base pay, this role may be eligible for other elements of Vertex’s total compensation package, which may include participation in the Vertex Bonus Plan (VOB), a role-specific sales commission or bonus, and/or equity grants, where applicable.\nLearn more about Life at Vertex and connect with your recruiter for more details regarding Vertex's compensation and benefit programs.\n*In all cases, compensation will comply with applicable local pay transparency and minimum wage requirements.","description_format":"text","description_chars":6195,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"Argentina","iso":"AR","kind":"country"},{"name":"Uruguay","iso":"UY","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Accounting & Tax Software"],"lifecycle":[{"event":"open","at":"2026-11-09T23:56:52Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":30,"reasons":["conf:0","win:early"],"computed_at":"2026-11-10T00:49:12Z"},"pay":null,"html_url":"https://alion.io/job/vertex-staff-data-engineer","json_url":"https://alion.io/job/vertex-staff-data-engineer.json","meta":{"generated_at":"2026-11-10T00:49:12Z","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":1761,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-11T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"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":58884},"rest":"https://alion.io/mcp/rest/get_company?id=58884"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fvertex-staff-data-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"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%2Fvertex-staff-data-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"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%2Fvertex-staff-data-engineer"},{"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/vertex-staff-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fvertex-staff-data-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3992422}},{"tool":"search_jobs","arguments":{"company":"vertexinc.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3992422},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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