{"id":176023,"url":"https://alion.io/job/regard-data-engineer","title":"Data Engineer","company":{"id":63147,"name":"Regard","domain":"regard.com","url":"https://alion.io/company/regard","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":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["New York, United States","San Francisco, United States","Los Angeles, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":190000,"currency":"USD","period":"year","gross":null,"usd_annual":190000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Iceberg","optional":false},{"name":"AWS","optional":false},{"name":"ClickHouse","optional":false},{"name":"Dagster","optional":false},{"name":"FastAPI","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Amazon S3","optional":true},{"name":"AWS Glue","optional":true},{"name":"CI/CD","optional":true},{"name":"GitLab CI","optional":true},{"name":"HIPAA","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM","optional":true},{"name":"Metabase","optional":true},{"name":"NLP","optional":true},{"name":"Pulumi","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-06-18T15:12:14Z","employer_posted_date":"2026-06-18","last_verified_at":"2026-10-17T14:43:13Z","board_verified":true,"closed_at":null,"days_open":121,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":120},"description":"As a Data Engineer at Regard, you'll build and maintain the data pipelines and infrastructure that turn raw clinical and product data into the metrics, insights, and capabilities that drive our product decisions, analytics, and AI research. We run an engineering-first stack that prioritizes transparent, code-driven systems over black-box services, and you'll contribute to the continued growth and reliability of our data platform.\nWorking closely with Product, Clinical, Engineering, and Research teams, you'll develop pipelines that bring disparate datasets together into cohesive models, support analytics initiatives, and help ensure the quality and availability of critical datasets. You'll work across the full data stack - from our AWS lakehouse to analytics, APIs, and research datasets - while growing your expertise in distributed data processing, data modeling, and platform operations.\nAbout Regard\nRegard's mission is to bring world-class healthcare to everyone. Our technology reasons through a patient's entire medical record to recommend diagnoses that would otherwise be missed, in real time at the point of care, during chart review, and in population-wide screening to identify patients who qualify for lifesaving treatment.\nWe work alongside some of the top health systems in the country to lead the change this industry needs. We're excited by challenges, mission-oriented work, and meaningful relationships. We want you to join us.\nOur Tech Stack:\nLakehouse & processing: Python, SQL, Amazon S3 and S3 Tables, Apache Iceberg, PySpark, EMR Serverless, AWS Glue, Athena\n\nOrchestration & infrastructure: Dagster, Kubernetes, Pulumi, GitLab CI/CD\n\nData services & analytics: PostgreSQL, ClickHouse, FastAPI, Metabase\n\nResponsibilities:\nBuild and evolve pipelines that make clinical, application, and reference data available for product development, analytics, and research\n\nDevelop and improve data models that bring disparate datasets together into reusable, cohesive views - revealing connections across clinical workflows and product activity\n\nPartner with Product and Clinical teams to explore datasets, develop meaningful measures of adoption and impact, and deliver insights through visualization\n\nOptimize data processing workloads and storage patterns, using experiments and benchmarks to improve performance, scalability, and cost efficiency\n\nBuild APIs, tools, and automation that make data easier to discover and use across the organization\n\nContribute data workflows and datasets that support clinical AI development and evaluation in partnership with Research and Engineering\n\nTake projects from idea through code review, testing, deployment, and production ownership - making the resulting datasets trustworthy, well-documented, and accessible under appropriate privacy controls\n\nMinimum Qualifications:\nBS in Computer Science, Mathematics, Statistics, a related field, or equivalent practical experience\n\n3+ years of experience in a data engineering role\n\nExperience building production data pipelines and bringing multiple data sources together into useful data models\n\nProficiency in Python and SQL, with experience using version control, automated tests, and code review to deliver maintainable software\n\nExperience with distributed data processing frameworks such as PySpark and cloud-based data platforms (AWS preferred)\n\nWillingness to participate in on-call operational support for owned systems\n\nPreferred Qualifications:\nExperience with Apache Iceberg or other lakehouse table formats, Dagster or a comparable orchestrator, and scalable data processing patterns\n\nFamiliarity with healthcare data, HIPAA requirements, de-identification, and standards such as FHIR, OMOP CDM, or ICD-10\n\nExperience translating product questions into analytical datasets and visualizations, or building data services with tools such as PostgreSQL, ClickHouse, or FastAPI\n\nPractical experience with LLM-assisted development, including reviewing generated code and independently validating results\n\nExposure to training and evaluation datasets, clinical NLP or LLM workflows, or tools that give AI assistants controlled access to data\n\nHybrid Work | Location | Work Authorization\nFor this role, Regard is currently only considering candidates who are authorized to work in the US without visa sponsorship, and are within the New York City, Los Angeles, or San Francisco metro areas\n\nWe expect our Engineers to be in the office on Tuesdays and Thursdays. We also require more frequent in-office work during the onboarding period and team onsite weeks up to once per month\n\nWe will provide relocation assistance to anyone who does not already reside in the NYC metro area\n\nWe prefer hiring people within commuting distance of our offices because we value getting together in person regularly\n\nFor those who enjoy working from our LA or Manhattan offices on a more regular basis, we offer catered lunches and other fun perks\n\nAdditionally, hybrid employees have the flexibility to work from locations outside of their home office from up to 6 weeks per year\n\nComp | Perks | Benefits\nEligible for equity\n\n99% employer paid health benefits (Medical, Dental, and Vision) + One Medical subscription\n\n18 PTO days/yr + 1 week holiday break\n\nMonthly health & wellness budget\n\nCompany-sponsored team retreat + social events\n\nA sabbatical program\n\nOur goal at Regard is to provide and maintain a work environment that fosters mutual respect, professionalism and cooperation. Regard is proud to be an equal opportunity employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, national origin, ancestry, alienage or citizenship status, age, disability or handicap, sex, gender identity, marital status, familial status, veteran status, sexual orientation or any other characteristic protected by applicable federal, state or local laws. We celebrate diversity and are proud of our supportive, inclusive workplace.\nAll candidates must successfully complete a background check as part of the hiring process.\nRecruitment Fraud Notice\nRegard only conducts hiring through official @regard.com email addresses. We will never ask candidates to pay fees, purchase equipment, or share sensitive personal information (such as Social Security numbers or bank details) during the interview process. If you receive an email about a job opportunity at Regard from a non-regard.com email address, it is not from us.","description_format":"text","description_chars":6454,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Home office","Hybrid work","Relocation assistance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["Medical AI","Clinical Decision Support"],"lifecycle":[{"event":"open","at":"2026-08-30T14:10:06Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.393,"p_room":0.28,"age_days":120,"expected_fill_days":32,"reasons":["conf:0","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":190000,"is_top_pay":true},"html_url":"https://alion.io/job/regard-data-engineer","json_url":"https://alion.io/job/regard-data-engineer.json","meta":{"generated_at":"2026-10-17T17:20:16Z","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":23841,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"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":63147},"rest":"https://alion.io/mcp/rest/get_company?id=63147"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fregard-data-engineer"},{"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%2Fregard-data-engineer"},{"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%2Fregard-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/regard-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fregard-data-engineer"}]}