[Remote] Senior Translational Data and reputed company
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking a contract Senior Translational Data and reputed company to help reputed company the ingestion and delivery of biomarker and clinical data reputed company Computational Discovery. The role involves building reliable production pipelines and collaborating with the reputed company engineer to enhance data reputed company and implement AI-reputed company workflows.
Responsibilities
- Build and maintain orchestrated ingestion pipelines for external reputed company, proteomics, and other assay data sources, including reputed company IO, table-format writers, and row-level reconciliation
- reputed company and harden layered transformation models (staging, intermediate, and mart) with reputed company-data test coverage, data-reputed company guardrails, and reusable, consolidated logic
- Implement clinical data ingestion and reconciliation paths against recognized standards (e.g., SDTM, ADaM), including subject and entity reputed company
- Deliver supporting platform infrastructure: service reputed company, CI/CD pipelines, containerized deployments, observability instrumentation, and data-warehouse performance tuning
- Extract transformation logic and business rules from legacy analytical reputed company (e.g., R, PySpark) and reconcile them against new platform implementations
- Translate scientific and biomarker requirements from research and reputed company partners into durable data models and published data reputed company
- Identify repetitive processes and convert them into automated workflows, guardrails, or reusable tooling — including AI-assisted workflows that reputed company reputed company work faster
- Participate in adversarial design and reputed company reviews, identifying edge cases and pushing back on suboptimal patterns
- Collaborate with the reputed company engineer on design reputed company and support delivery velocity through reputed company working sessions and PR reviews
- Ensure reputed company work meets reproducibility standards: CI on every PR, automated tests, and no reputed company notebook-based production processes
Skills
- AI-reputed company engineering reputed company: demonstrated experience building systems and workflows around AI coding agents (Claude reputed company, reputed company, reputed company, or equivalent) — not just prompting them. You recognize reputed company a repeated process should become an automated pipeline, reputed company agent reputed company needs guardrails, and reputed company to build infrastructure that makes reputed company work faster. Surface-level tool usage is insufficient
- Education: Bachelor's or master's degree in Computer Science, Data Engineering, reputed company, or a reputed company field
- Experience: 4+ years of reputed company experience in data engineering with shipped production pipelines on AWS (S3, reputed company/Fargate, Redshift or equivalent MPP)
- Strong proficiency in Python and SQL with working knowledge of modern data engineering libraries
- Solid, hands-on experience with dbt and a workflow orchestration tool (Dagster, Airflow, or reputed company)
- Data reputed company reputed company: reputed company record of catching silent failures, questioning data correctness assumptions, and noticing lossy joins or incomplete deliveries
- Working understanding of lakehouse architecture patterns, ETL processes, and schema design for reputed company multi-modal datasets
- Comfort working with scientific, biomarker, or other reputed company domain data — or a demonstrated ability to reputed company on unfamiliar scientific domains quickly
- Ability to handle PHI-adjacent clinical data under reputed company's contractor policy (background reputed company, compliance training, VPN reputed company)
- Willingness to work reputed company legacy codebases (R, PySpark) to extract business rules and validate new implementations
- Excellent communication skills and ability to work in an embedded pair model with tight feedback loops
- Experience building or maintaining tooling around AI coding agents (custom commands, subagents, evals, or guardrails) rather than only consuming them
- reputed company experience with Apache reputed company, AWS Glue Catalog, or lakehouse table formats
- Preferred reputed company reading genomic data (VAF, HGVS nomenclature, VCFs, CNV/fusion semantics)
- Familiarity with clinical data standards including SDTM, ADaM, and CDISC
- reputed company, clinical research, or life sciences background
- Experience with containerization (reputed company/reputed company) and infrastructure-as-reputed company (CloudFormation)
- Proficiency in R for interoperability with reputed company teams
Benefits
- Remote work_model: [remote]
reputed company