{"id":2415923,"url":"https://alion.io/job/terradot-data-engineer","title":"Data Engineer","company":{"id":173602,"name":"Terradot","domain":"terradot.earth","url":"https://alion.io/company/terradot","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["São Paulo, Brazil"],"countries":["BR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Dagster","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"AWS","optional":true},{"name":"CI/CD","optional":true},{"name":"dbt","optional":true},{"name":"GCP","optional":true},{"name":"GDAL","optional":true},{"name":"PostGIS","optional":true},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-08-19T21:05:29Z","employer_posted_date":"2026-08-19","last_verified_at":"2026-10-13T17:22:21Z","board_verified":true,"closed_at":null,"days_open":54,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":54},"description":"Our mission is to stabilize Earth’s climate by transforming nature’s most powerful permanent carbon removal process into a global climate solution. By advancing science, building technology, and assembling a global coalition, we are catalyzing an initiative to scale Enhanced Rock Weathering within the next decade, starting in Brazil.\nFounded out of the Stanford University ecosystem, Terradot brings together expertise from industry, academia, and government to advance the science and technology of Enhanced Rock Weathering.\nTerradot has raised $58.2 million in funding from investors including John Doerr, Sheryl Sandberg and Tom Bernthal, George Roberts, Microsoft’s Climate Innovation Fund, Google, Cisco, Floodgate, Kleiner Perkins, Acre Venture Partners, Gigascale Capital, Valor Capital, Ponderosa Ventures, and others. We have sold approximately 300,000 tons in offtakes to carbon removal buyers including Frontier and Google.\nAll qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other characteristic protected\nAbout the role\nTerradot is seeking a Data Engineer to help build and operate the data infrastructure that supports our scientific and operational work.\nYou will focus on moving data reliably from field, laboratory, operational, and external sources into well-structured, accessible data systems. Your primary responsibilities will include data ingestion, pipeline development, workflow orchestration, warehouse modeling, testing, and monitoring.\nThis role is well suited to an engineer in their second or third professional role who has developed a solid software engineering foundation and is ready to take greater ownership of production data systems. You do not need to arrive as an expert in climate, geospatial data, or Enhanced Rock Weathering. You should be excited to learn the domain and apply strong engineering practices to complex real-world data.\nYou will work closely with data scientists, software engineers, scientists, and operational teams to ensure that trusted data is available for analysis, modeling, measurement, and decision-making.\nWhat you'll do\nBuild and maintain data pipelines that ingest information from field operations, laboratories, internal applications, vendors, APIs, and public datasets.\nDevelop and operate orchestrated workflows for recurring ingestion, transformation, validation, and delivery processes.\nDesign clear, maintainable data models within Terradot’s data warehouse.\nImprove the reliability, performance, and usability of data used by scientific and operational teams.\nImplement automated testing, monitoring, alerting, and documentation for production data workflows.\nInvestigate pipeline failures, data quality issues, and inconsistencies across source systems.\nBuild reusable integrations and tools that reduce manual data movement and improve self-service access.\nCollaborate with data scientists to productionize the datasets and transformations required for geospatial and statistical analysis.\nContribute to shared engineering standards through code review, testing, documentation, and thoughtful system design.\nHelp improve how Terradot manages data lineage, permissions, schemas, and ownership as our systems scale.\nWhat we are looking for\nProfessional experience building or maintaining production software or data systems, typically gained through a second or third engineering role.\nStrong programming skills in Python and working proficiency in SQL.\nExperience building data pipelines, backend services, API integrations, or automated data workflows.\nFamiliarity with at least one workflow orchestration system, such as Airflow, Dagster, or Prefect.\nExperience working with relational databases and data warehouses.\nUnderstanding of software engineering fundamentals, including version control, testing, code review, debugging, and maintainable system design.\nAbility to investigate problems across the full data lifecycle, from source systems through transformed datasets.\nClear communication skills and an interest in working with colleagues from scientific, operational, and commercial backgrounds.\nFluent English communication skills\nComfort working in an environment where requirements may evolve as the science and operations develop.\nWe value demonstrated ability and growth potential more than experience with a particular technology stack.\nNice to Have\nExperience with dbt or similar data transformation frameworks.\nFamiliarity with cloud platforms such as AWS or GCP.\nExperience with containerization, infrastructure as code, or continuous integration and deployment.\nExposure to geospatial data or tools such as PostGIS, GDAL, GeoPandas, rasterio, Zarr, or STAC.\nExperience working with sensor, laboratory, agricultural, environmental, or operational data.\nFamiliarity with data observability, metadata management, or lineage systems.\nPersonal Attributes\nPractical and action-oriented, with a focus on building systems that work reliably.\nCurious about unfamiliar scientific and operational domains.\nComfortable asking questions and making ambiguity more concrete.\nThoughtful about balancing immediate delivery with maintainable engineering.\nCollaborative and receptive to feedback.\nMotivated by measurable improvements in reliability, accessibility, and team effectiveness.","description_format":"text","description_chars":5393,"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":"Advanced (C1)","optional":false}]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["ESG & Carbon 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