• Analyze and consolidate historical workforce, FTE, and timekeeper data from multiple source systems. • Design and develop automated data conversion and transformation processes to reduce manual effort and improve data quality. • Extract data from APIs, databases, flat files, and other structured and unstructured sources. • Perform data cleansing, standardization, validation, and enrichment activities to ensure data integrity. • Transform and map source data to align with target system requirements and reporting standards. • Produce standardized output files and datasets that conform to the target application's native data model. • Partner with business stakeholders to gather requirements and translate business needs into technical data solutions. • Conduct data quality assessments, reconciliation, and validation activities throughout the migration lifecycle. • Support testing, dry-run conversions, and production migration activities. • Troubleshoot data issues and implement corrective actions as needed. • Document data mappings, transformation rules, conversion logic, and validation procedures. • Collaborate with project managers, business analysts, and client stakeholders to ensure successful project delivery.

• Deliver production-ready datasets and pipelines to support data science and analytics. • Bridge the gap between ML experimentation and deployment with MLOps best practices. • Build and deploy data-driven applications using Azure services. • Maximize ROI on Azure investment through cloud-native architecture. • Standardize development workflows using GitHub (version control, pull requests, CI/CD). • Automate deployments and accelerate engineering velocity with GitHub Actions. • Reduce bottlenecks for analysts, engineers, and data scientists by improving data accessibility and workflow efficiency. • Enhance data quality, governance, and observability. • Enable future capabilities such as AI, automation, and personalization.

Role Description Assists with safety, pharmacovigilance and regulatory activities including (but not limited to): - Medical Dictionary for Regulatory Activities (MedDRA) coding - Data management activities which includes cleaning and validation of data - xEVMPD product dictionary - Substances, Products, Organizations and Referential (SPOR) / Identification of Medicinal Products (IDMP) data cleansing - Data mapping, data enrichment and data validation activities All activities must adhere to: - Data privacy guidelines - Good Clinical Practice (GCP) - Good Pharmacovigilance Practice (GVP) - Regulatory guidelines - Company and project/program-specific procedures for clinical trials and/or post-marketing safety programs The processing of information may include: - Filtering - Cleansing - Migrating - Analyzing - Reporting - Filing or publication of data and information Qualifications - Bachelor’s degree in scientific field (Life Sciences degree) - 2+ years in scientific/clinical research background with experience in Data handling/Data validation/Regulatory processes - English fluency to collaborate with regional and global teams Requirements - Review existing system data against reference sources - Identify discrepancies and update records per project regulatory guidelines - Analyze data based on BU reference standards - Focus on accurate processing and maintenance of structured data - Update incomplete fields - Create or submit missing information - General data entry and quality improvement Benefits - Passionate about developing our people through career development and progression - Supportive and engaged line management - Technical and therapeutic area training - Peer recognition and total rewards program - Commitment to building an inclusive culture

Role Description As a Software Engineer on our Data Platform team, you will drive the evolution of our identity data backbone, the systems every Lumos product depends on. You will be instrumental in building robust, scalable, and reliable platform software. You will play a key role in designing and operating the software that turns raw identity inputs into a trusted foundation for the product. We’re a startup that values ownership, curiosity, and trust—and we’re looking for engineers who love building platform infrastructure that enables teams to move faster while improving resilience and visibility. - Design, develop, and operate systems that transform high volumes of identity data from third-party integrations to product consumers with correctness, freshness, and operational rigor. - Build the shared primitives and interfaces (APIs, services, materialized models) that abstract raw identity data into the building blocks that power our products. - Contribute to the technical vision for a world-class data infrastructure that empowers engineering, product, and AI teams, enabling seamless access to high-quality data. - Establish SLOs, observability, and operational tooling that catch and remediate failures in identity data systems before they reach customers. - Promote and implement software engineering best practices for building scalable, reliable, and secure data-centric applications. Elevate the principles of software engineering within the data domain. Qualifications - 3-7 Years of experience as a backend or platform engineer building production data systems other teams depend on, either ingestion and sync pipelines (Dagster, Airflow, or comparable orchestration) or service layers in front of a transactional database (MySQL/Postgres) that abstract storage from internal consumers. - Strong backend development skills in Python, Go, or TypeScript, with a focus on clean API design, testability, and observability. - Strong instinct for data correctness, observability, and SLOs in systems where downstream products take action on the output. - Experience designing service or API interfaces over a transactional datastore (MySQL/Postgres) defining contracts that let producers and consumers evolve independently. - Familiarity with identity and access governance (IGA) data (e.g. identities, accounts, entitlements, group memberships) and how its correctness, freshness, and traceability shape downstream governance outcomes at scale. Benefits - Remote-first culture – Work from anywhere within ±4 hours of Pacific Time. - Medical, dental & vision insurance – 100% of premiums covered for employees, 60% for dependents. HSA and FSA available with employer contribution. International benefits align with local standards. - Mental health support – Access to mental health resources and support. - Monthly wellness stipend – A monthly stipend for gym memberships, fitness apps, and whatever helps you recharge. - Life & disability insurance – Life insurance, short-term disability, and long-term disability coverage available. - Flexible PTO – Flexible time off with a minimum annual requirement, because rest is part of doing your best work. - Parental leave – Up to 16 weeks of paid parental leave for expecting parents. - $1,000 annual learning stipend – An annual budget for courses, books, conferences, and certifications. - Company & team offsites – Company and team bonding trips throughout the year, fully covered by Lumos. - 401(k) with matching – Employer 401(k) matching to help you save for the future. Company Description Lumos is the industry's first Autonomous Identity Platform — software that doesn't just surface access risk, but acts on it. We started with a self-service AppStore and grew into the critical infrastructure connecting apps, identities, and data for GitHub, MongoDB, Mars, Pinterest, Anduril, Intercom, Roku, and Netskope. At the center is Albus, our AI agent for identity — mining roles, approving access, and catching the drift humans miss. Since launching out of stealth in April 2022, we've grown from 20 to ~130 Alchemists and raised over $65M from a16z, Scale, Neo, Greg Brockman (President at OpenAI), and Phil Venables (CISO at Google). Named a Strong Performer in the 2026 Gartner Voice of the Customer for IGA — 4.7/5, with 96% of reviewers saying they'd recommend us. Our customers cut time-to-access by 98%, slash IT tickets by 72%, and eliminate excess privilege at scale. Three years running on Forbes' Top 100 Best Startup Employers in America (2024, 2025, 2026) — measured on culture, retention, growth, and job creation.