As aSenior Data Standards EngineeratEvinova,you'llarchitect andoperatethe automated pipelines that keep our Data Platform current with evolving clinical dictionaries and reference datasets - from CDISC controlled terminology releases to FHIR value sets and ICH M11 updates. Your work will be the backbone of how clinical study protocols(CSPs)are interpreted, designed and monitored acrossEvinova'sexpandingcustomerportfolio.

This is a senior engineering role with genuine scope:you'llset technical direction, drive automation-first thinking, and mentor a high-calibreteam - all in a fast-moving health tech environment where your decisions directly influence how medicines reach patients.

What if every time a clinical data standard was updated, your platform simply knew - and adapted automatically, with no human intervention required? That'sthe challengeyou'llown.

You'lljoin ahigh-performing, globally distributed Data Platform team. We work in agile/scrum cycles, deploy on AWS, and hold ourselves to engineering standards that support both regulated (GxP) and innovation-track workstreams.

Accountabilities/Duties:

Automated Standards Ingestion - Zero Human Intervention

Your primary mission iseliminatingmanual effort from thestandardslifecycle. You will:

• Design and ownfully automated ELT/ETL pipelinesthat detect, ingest,validate, and publish new releases of clinical dictionaries (e.g., MedDRA, WHO Drug, SNOMED CT, CDISC CT, NCI Thesaurus) without human intervention

• Buildevent-driven and scheduled pipeline architectureson AWS (Lambda, Step Functions, Glue, S3,EventBridge) that react to upstream standard releases and propagate changes downstream automatically

• Implementautomated versioning and change detectionso downstream consumers always know what changed,what'snew, andwhat'sbeen deprecated - and can act on it programmatically

Clinical Standards Architecture

• Apply deepexpertiseinUSDM, ICH M11, FHIR, and CDISC (SDTM/ADaM/CDASH)to definecanonicalschemas, mapping strategies, and versioning models for clinical dictionaries and controlled vocabularies

• Designoptimizeddata stores(relational, columnar, graph asappropriate)for serving clinical reference data at query speed - including schema design, indexing, partitioning, and performance tuning

• Model how terminology, code lists, and controlled vocabularies relate across standards and internal systems, enabling consistent coding and reporting across all clinical workflows

AI & Machine Learning Integration

• ImplementAI-assisted mappingbetween dictionaries and source systems - surfacing high-confidence automated mappings and flagging exceptions for review

• DeployML-based anomaly detectiontoidentifyinconsistencies, unexpected changes, or quality issues across ingested standards data

• Explore and productionizeLLM-assisted toolsfor standards interpretation, change summarization, and intelligent workflow automation

Technical Leadership & Stakeholder Influence

• Setengineering best practicesfor the data standards domain - pipeline design patterns, testing strategies, infrastructure-as-code, observability, and documentation standards

• Serve as thetechnical authorityon clinical data standards for the Data Platform team, providing guidance to clinical operations, data management, biostatistics, safety, and regulatory functions

• Communicate complex standards and data engineering concepts clearly to both technical and non-technical audiences - from engineers to clinical leads to senior leadership

• Mentor and upskill team members, fostering a culture of automation-first engineering and continuous improvement

Essential Skills & Experience:

Data Engineering & Automation

• 8+ years in data engineering or software engineering, with a strongtrack recordof delivering production-grade ELT/ETL pipelines for complex, regulated data domains

• Demonstratedexpertisebuildingfully automated, event-driven pipelinesthatoperatewithout human intervention in steady state

• ProficiencyinPython(primary) and/orTypescriptor Java; advanced SQL; infrastructure-as-code (Terraform, AWS CDK, or equivalent)

• Deep, hands-on AWS experience: S3, Glue, Lambda, Step Functions,EventBridge, RDS - and the architectural judgment to choose the right service for the job

• Strong database design skills across relational and columnar stores - schema design, query optimization, partitioning, indexing

Clinical Data Standards

• Thorough, hands-on knowledge ofCDISC (SDTM, ADaM, CDASH),FHIR,USDM, andICH M11, and how controlled terminologies are implemented in practice across clinical trial workflows

• Proven fluency interminology mapping- semantic alignment, code-list mapping, managing evolving and inconsistent terminologies across standards and source systems

• Practical understanding of how clinical dictionaries (MedDRA, WHO Drug, SNOMED, NCI Thesaurus, CDISC CT) are structured, versioned, and applied across the study lifecycle

AI/ML Application

• Experience applyingAI or ML techniquesto data engineering challenges - automated mappings, anomaly detection, intelligent quality checks, or NLP-based standards analysis

• Ability to evaluate and integrateLLM-based toolsinto engineering workflows where they add genuine, measurable value

Leadership & Communication

• Demonstrated ability to set technical direction and mentor engineers in a senior/lead capacity

• Exceptional communicator - able to influence cross-functional stakeholders and translate between engineering and clinical/regulatory domains

• Comfortoperatingin agile/scrum teams; fluent with Jira, Confluence, and related tooling

• Experience working in or alongsideGxP-regulated environments, with understanding of validation, audit trail, and documentation requirements

Preferred Qualifications:

• Advanced degree (Master'sor PhD) in Computer Science, Bioinformatics, Data Engineering, Life Sciences, or related field

• Direct pharma/biotech, CRO, or clinical technology experience, particularly in data standards or data engineering functions

• Familiarity withmetadata repositoriesand standards governance processes (e.g., CDISC Library API, NCI EVS)

• Experience withadditionalstandards:CDASH, SEND, HL7 v2/v3, OMOP CDM

• Background in platform or product engineering - thinking beyond pipelines to reusable services and APIs that teams consume

WhyEvinova?

Evinovasits at a rare intersection: the scientific credibility and scale of AstraZeneca, with the engineering culture and pace of a health tech company. Youwon'tbemaintaininglegacy systems -you'llbe building the infrastructure that defines how clinical data standards are consumed across an entire enterprise, with AI accelerating everything.

• Real impact:Your pipelines will directly influence how clinical trial data is coded, analyzed, andsubmittedto regulators globally

• Engineering-first culture:Automation, clean architecture, and technical craft are valued - not just delivery velocity

• Global scale, startup pace:Work with a distributed, high-calibreteam across multiple continents, with the resources of atop-5global pharma behind you

• Growth:Evinovais still building. The decisions you make now will shape the platform for years

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Are you alreadyimagining yourselfjoining our team? Good, because wecan'twait to hear from you.