{"id":2738901,"url":"https://alion.io/job/prolaio-sr-data-engineer","title":"Sr. Data Engineer","company":{"id":688731,"name":"Prolaio","domain":"prolaio.com","url":"https://alion.io/company/prolaio","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chicago, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":112000,"max_usd":214000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1181},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"Datadog","optional":false},{"name":"dbt","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"GitLab CI","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Kubernetes","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Google Cloud Run","optional":true},{"name":"HIPAA","optional":true},{"name":"IAM","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-16T18:04:28Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-16T23:50:31Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Who Are We?\nProlaio believes that continuous learning and collaboration can make a significant difference in how heart care is administered. We are creating smarter ways to address heart disease and heart risks by uniting patients, care teams, and researchers on a secure, technology-enabled platform that drives clinical innovation and offers a path towards better patient outcomes.\nThis is precision cardiology, and we know it’s within reach.\nWhat Will You Do?\nThe Overview\nAs a Senior Data Engineer, you will design, build, and run that pipeline in a regulated environment. You will work closely with the data science/clinical teams, which owns the medical and research questions. You will also work with the Data Architect on platform standards, data models, and governance.\nThe Specifics\nBuild and Evolve the Data Platform (Prolaio Data Ecosystem)\nDesign, build, and maintain batch, streaming, and hybrid pipelines orchestrated with Dagster. These cover ingestion, validation, transformation, enrichment, and publishing of the data.\nDevelop and maintain dbt models in BigQuery, including staging, intermediate, and mart layers, with tests, documentation, and clear ownership.\nIngest and normalize heterogeneous sources (both structured and unstructured data), including cardiology wearables and device signals, EHR, claims, medication, and patient-reported data.\nMake well-reasoned decisions about storage, compute, partitioning, cost, and APIs, and contribute to the target-state architecture and the reference patterns.\nData Quality, Lineage, and Compliance\nContribute to data lifecycle controls into pipelines: retention, access control, lineage, provenance, reproducibility, and auditability.\nUse Dagster assets and dbt lineage to keep data traceable from source to output.\nSupport validated operation in a regulated setting by documenting pipelines, keeping traceability, and working with Quality and Security teams.\nBack every pipeline change with thorough automated tests and data quality checks.\nEnable Data Science and ML\nTreat data scientists as your customers, and give them the tools and processes to experiment and iterate efficiently.\nContribute to the ML workflows that support feature generation, training, deployment, and monitoring.\nContribute to internal applications and Python libraries\nOperate and Monitor\nOwn CI/CD for the data platform using GitLab CI, including dbt and Dagster deployments.\nHelp monitoring pipeline health, performance, and BigQuery cost with Datadog, and take part in incident response.\nHelp mentoring other engineers and setting engineering standards for the data team.\nWhy Prolaio?\n Impactful Work: You will join in the fight against heart failure (HF) and hypertrophic cardiomyopathy (HCM) with the goal of extending and saving the lives of our patients while also being at the forefront of changing the healthcare industry through technology.\nInnovative Environment: You will be part of an organization doing something that’s never been done before.\nProfessional Growth: You will join a growing team and have a substantial impact on our daily and future operations with the opportunity to continuously learn and grow.\nCollaborative Team: You will be part of a team of collaborative, curious, and committed individuals focused on the collective good, inclusiveness, scientific excellence, and advancing digital health for cardiology.\nWho You Are?\n6+ years in data engineering\nExpert Python and SQL\nExperience with GCP (or AWS/Azure)\nProduction experience with dbt, including modeling, testing, macros, and incremental models.\nExperience with BigQuery or a comparable cloud data warehouse (Databricks, Redshift).\nExperience with Dagster or a comparable orchestrator (Airflow, Prefect).\nExperience with Docker and large-scale data processing.\nExperience with structured, semi-structured, and unstructured data, including time-series data.\nUnderstanding of MLOps concepts and production ML workflows.\nExperience collaborating with data scientists, product, and clinical or quality stakeholders.\nExperience with Docker and Kubernetes.\nAdditional Qualifications (Nice to Haves)\nHands-on GCP experience (IAM, Cloud Storage, Cloud Run, Pub/Sub, networking).\nInfrastructure as code with Terraform\nExperience with Datadog\nMetadata, lineage, and catalog tools, plus retrieval or vector tooling for AI use cases.\nExperience with Databricks\nExperience working with healthcare, life sciences, medtech, or other patient data.\nExperience in regulated or validated environments (SaMD, FDA, GxP, HIPAA).\nStreaming tools such as Pub/Sub or Kafka.\nWhy You’ll Love Working Here\nMeaningful Compensation: Competitive salary, performance bonus, and equity so you can share in what we build.\nGreat Health Coverage: Medical, dental, and vision plans with multiple options and strong company contributions.\nFlexible Spending Perks: HSA, FSA, commuter benefits, and a $1,200 annual Lifestyle Spending Account to support wellness, commuting, family needs, and more.\nTime to Recharge: Generous paid time off, sick leave, and company holidays.\nFamily-First Benefits: Paid parental leave, caregiver leave, and support for growing families.\nSecurity & Peace of Mind: Company-paid life insurance and short- and long-term disability coverage.\n Plan for the Future: 401(k) plan to help you build long-term financial security.\n Care When You Need It: Easy access to telehealth and optional supplemental coverage for life’s unexpected moments.\nStarting Salary is at $150,000.00 (Exact Compensation may vary based on skills, experience, and location)","description_format":"text","description_chars":5563,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Equity","Life 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