{"id":1231292,"url":"https://alion.io/job/adoreal-senior-data-engineer","title":"Senior Data Engineer","company":{"id":8600,"name":"Adoreal","domain":"adoreal.com","url":"https://alion.io/company/adoreal","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-30T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":120000,"max_usd":208000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":212},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"BigQuery","optional":false},{"name":"Claude Code","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Fivetran","optional":false},{"name":"GDPR","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Great Expectations","optional":false},{"name":"HIPAA","optional":false},{"name":"LLM","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-09-25T14:50:30Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-09-30T04:19:03Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Who We Are\nWe are a fast-growing vertical SaaS company leveraging innovation and disruptive technologies to improve consumer experiences, outcomes, and predictability within the plastic surgery industry. Our team thrives on challenges, embraces change, and is dedicated to transforming how the industry operates.\nData is a critical product within our company, and we are investing heavily in our data capabilities. Our platform is what aesthetic medicine and plastic surgery practices run their business on, covering scheduling, clinical records, forms and consents, invoicing and payments, patient communications, and the marketing that sits in front of all of it. It is a multi-tenant platform holding millions of patient records under HIPAA and GDPR, and we onboard new practices every month.\nOur job is to give patients an experience that feels considered at every step, to make the practice itself run efficiently, and to grow that practice as a result. Data is what makes all three possible. A patient's journey with a practice runs from first lead through consultation and procedure to follow-up, and a practice can only improve that journey, staff against it, and invest behind it when the numbers describing it are right. Getting that picture back to our clients accurately is a large part of what they pay us for. Every practice that joins us arrives by migrating off a legacy system, so migration here is ongoing work rather than a one-time project.\nWhile we are a remote-first company, we are currently only able to hire candidates located in the following U.S. states: CA, CO, FL, GA, IL, MN, OK, OR, PA, RI, TX, UT, and WA. We hope to expand to additional states in the future.\nWho We're Looking For\nWe are seeking a Senior Data Engineer to be the most experienced engineer on our data team. This is a hands-on role by design. You will pair with the team daily, set the standards the data function works to, and take the lead on the architecture decisions that shape what we build next.\nThe remit is broad. You will own the target design for the warehouse and the curated layer that sits on top of it, define the semantic layer so that every business metric carries one agreed definition, and establish the standards for naming, lineage, and data quality that the whole function works to. All of it serves the same end. A practice should be able to see the patient journey clearly enough to improve it, see where its time and capacity actually go, and know which of its decisions grew the business. You will also take migration from something skilled people do carefully to something the platform does repeatably.\nOur warehouse is Amazon Redshift running a medallion model, fed from PostgreSQL by Python pipelines and from marketing sources by Fivetran, with Power BI on top. You will own the recommendation on where that architecture goes next, and then you will build it.\nWe also build with AI as a default rather than as an experiment. Coding agents draft quickly here, so the skill we hire for and level on is knowing what to build and recognizing what is wrong with a draft. Our data team already works with Claude Code connected to the warehouse every day.\nAs the Senior Data Engineer, you will:\nArchitecture and Modeling\nOwn the target architecture for the warehouse and the curated layer, decide where that design goes next, and write down the reasoning behind the call. \nDesign the semantic layer as a single metric repository, where each business metric means one thing and the definition, the formula, and the reasoning behind it are all recorded. \nSet the standard for naming, labeling, and lineage, and bring enumerated values and business rule history into data the warehouse can resolve directly. \nBuild the configuration model for practice-specific business rules, so that each new practice's setup arrives as data the platform can apply. \nBuilding With the Team\nPair with the data engineers daily. Review their work in a way that teaches, and let them review yours. \nBuild the gold layer and a baseline report library that every new practice gets from day one, covering the patient journey, practice capacity, and growth. \nExtend infrastructure as code and CI across the warehouse and its pipelines, with tests that catch schema drift when the product changes. \nBring the unstructured clinical record into the warehouse in structured form, including the journals, notes, and form submissions that arrive as HTML and PDF. \nAutomation and AI in the Data Platform\nDeepen the automation around migration profiling, delta reconciliation, data quality checks, and report provisioning. \nPut AI to work inside the pipelines for enrichment, anomaly detection, and metadata generation, including a data dictionary and enum catalog that stay current because they are generated. \nMake the warehouse safe and useful for AI. That means a complete catalog with descriptions and enumerations, a semantic layer that natural language queries resolve against instead of raw tables, a golden set of questions that measures accuracy before business stakeholders get access, and strict adherence to the rules governing which tools may touch patient data. \nMigrations and Partnership With Engineering\nTake migration from something skilled people do carefully to something the platform does repeatably, with pre-migration profiling, a matching framework for post go-live deltas, LLM-assisted schema mapping and record matching where it earns its place, and rejected record reporting so that nothing is dropped silently. The design target is two practice go-lives a month. \nPartner with the engineering teams on the platform changes the data function depends on, and define with them the change contract that keeps the platform and the warehouse in step as new fields and statuses ship. \nWork directly with product and commercial leadership on what to measure, not only on how to measure it. You should be the person who can tell a stakeholder which number actually says whether the patient experience improved, whether the practice got more efficient, or whether it grew. \nRequirements\n8+ years in data engineering, including end to end ownership of a warehouse or lakehouse architecture, from ingestion through to the curated layer that people actually query. \nDeep SQL and Python, with production experience on a modern cloud warehouse. Redshift is what we run today, and Snowflake, BigQuery, or Databricks experience transfers. \nHands-on experience building a semantic or metrics layer yourself, using dbt or an equivalent tool.\nProduction experience with orchestration and infrastructure as code on AWS (e.g., Airflow and Terraform).\nExperience designing and maintaining dimensional or Data Vault models in production.. \nData quality testing and observability built into the pipeline, using dbt tests, Great Expectations, or an equivalent, alongside daily use of coding agents and AI tooling in your own work. \nAI applied inside a data platform, such as LLM classification of unstructured records, entity matching, anomaly detection, or natural language querying over a semantic layer, with an evaluation set that told you how well it worked. \nExperience with regulated data, such as healthcare or financial data. \nBenefits\nWhat We Offer\nAt Adoreal, we believe in supporting our team’s well-being and growth through comprehensive benefits and a collaborative, people-first culture. As a globally remote company, we prioritize flexibility, inclusivity, and teamwork rooted in the Adoreal principles.\nBenefits & Perks:\n Healthcare coverage for you and your family \n401k Plan\n Paid time off (PTO) and paid holidays \n Company equity opportunities \n Fully remote work environment with flexible schedules \n Collaborative and thriving team culture guided by Adoreal’s core values\nWhy Adoreal?\nJoining Adoreal means becoming part of a high-performing, ambitious team that works hard, achieves extraordinary results, and enjoys the rewards that follow. Every employee receives equity, aligning us all in our shared success. Promotions and growth opportunities are limitless, driven only by your performance and dedication to our core principles:\nWe do what is best for the company, not what is best for individuals of the company-we take pride in our work, but not in pride itself-the success of Adoreal is more important than our egos.\nWe always share relevant information and admit our mistakes freely and openly (even when it is worrisome or uncomfortable to do so). Candid communication and a solution-oriented mindset is rewarded.\nWe innovate by finding the right problems, then solving them. We thrive on change that minimizes complexity and improves situations for our stakeholders.\nWe incentivize efficient results & people over process and focus only on the work that creates the most value for our stakeholders.\nWe are quietly confident and openly humble, being tenacious in our quest to perform and inspire others with our thirst for excellence.\nWe do not bow up and knock down-we care about our teammates and treat all of them with respect, regardless of their level within the company.\nWe are steadfast in our pursuit to better our company, our colleagues, and ourselves. When we hire, we only hire people who bleed our principles and who will hopefully be our replacement one day.\nAt this time, Adoreal is not offering visa sponsorship for this position. Candidates must have current and valid authorization to work in the country where they are applying. We comply with all applicable employment and immigration laws, including U.S. regulations, and encourage applicants to verify their work authorization status before applying.\nAdoreal is an equal opportunity employer committed to fostering a diverse, inclusive, and fair workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, marital status, veteran status, or any other protected characteristic under applicable U.S. law (EEOC) or local employment regulations where we operate. We encourage applications from candidates of all backgrounds.\nAccommodations for disabilities are available upon request throughout the recruitment process.\n*We are not working with search firms for this role, thank you*\nRecruitment Fraud Notice\nAdoreal has become aware of fraudulent job offers being sent by people falsely claiming to represent us. To protect yourself:\nVerify the sender's email address matches our official domain before responding.\nBe cautious of offers that come with no prior application or interview process.\nNever share personal details, banking information, or Social Security numbers as part of a job offer or interview.\nLegitimate offers will never ask you to pay money upfront for equipment, training, or onboarding.\nIf something feels off - urgency, poor grammar, unusual payment requests - trust your instincts and pause before responding.\nIf you receive a suspicious email or offer claiming to be from Adoreal, please don't respond to it directly. Report it as spam through your email provider and reach out to us at  with any concerns.","description_format":"text","description_chars":11143,"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":[]},"benefits":["401k plan","Equity","Flexible schedule","Growth opportunities"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Florida","iso":null,"kind":"city"},{"name":"Texas","iso":null,"kind":"city"},{"name":"Illinois","iso":null,"kind":"city"},{"name":"Utah","iso":null,"kind":"city"},{"name":"Pennsylvania","iso":null,"kind":"city"},{"name":"Oklahoma","iso":null,"kind":"city"},{"name":"Minnesota","iso":null,"kind":"city"},{"name":"Washington","iso":null,"kind":"city"},{"name":"Oregon","iso":null,"kind":"city"},{"name":"Colorado","iso":null,"kind":"city"},{"name":"Rhode Island","iso":null,"kind":"city"},{"name":"Georgia","iso":null,"kind":"city"},{"name":"California","iso":null,"kind":"city"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Health Care","Aesthetic Medicine & Plastic Surgery"],"lifecycle":[{"event":"open","at":"2026-09-25T14:50:30Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":4,"expected_fill_days":37,"reasons":["conf:1","velocity","win:early"],"computed_at":"2026-09-30T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/adoreal-senior-data-engineer","json_url":"https://alion.io/job/adoreal-senior-data-engineer.json","meta":{"generated_at":"2026-09-30T06:15:24Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4316,"day_limit":5000,"remaining_today":684,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}