Senior Engineer, Data Informatics

Eikon Therapeutics is a new biopharmaceutical company employing revolutionary technology at the intersection of chemistry, engineering, computation, and biology to discover novel treatments for life‑threatening diseases. Eikon’s discovery platform is built on groundbreaking innovations from its founders (Nobel Prize, 2014), culminating in the creation of microscopes which enable real time, molecular‑resolution measurements of protein movement in living cells, thereby unlocking otherwise intractable classes of proteins as drug targets.

We are currently seeking an experienced informatics engineer to contribute to the design, implementation, and development of our informatics processes and systems to support all phases of our research pipelines. You will work closely with our scientists and engineers to capture and manage functional requirements. You will be a core member of a team that is responsible to build scalable solutions to fulfill these requirements that fit into our information ecosystem and ensure the integrity of our data architecture.

You are agile of mind and effectively communicate difficult concepts. You work well within a fast‑paced, mission‑driven, dynamic environment. You are prepared to tackle a broad selection of challenges as the company grows, and possess a deep desire to pursue creative solutions with broad guidance and a high degree of independence. You can partner with R&D leadership and functional area scientists to proactively identify areas of need, design solutions, prioritize work, coordinate pilot studies, ensure appropriate system usage, and regularly report on system metrics and portfolio execution.

• Actively involved in the administration and integration of LIMS software and AI/ML platform into R&D projects and systems.
• Contribute to the design, development, test, and implementation of informatics solutions including LIMS, ELN, Inventory Management, etc.
• Implement data warehouse / data lake systems and pipelines for advanced analytics and AI/ML strategy.
• Implement data automation pipelines and ETL processes.
• Collaborate with a cross‑functional team to develop an end‑to‑end digital architecture roadmap.
• Work with project stakeholders to analyze data management, analytics, and visualizations needs across R&D functions.
• Gather user stories, design applications, implement and integrate systems and guide the functionality of IT systems across the company.
• Ensure that systems are fully documented with system requirements, architectural design, and operational plans.
• Coordinate the training and support of end‑users on system usage and best practices.
• Responsible for application licenses and forecasting annual usage.
• Participate in design of enterprise‑wide data platform architecture and ensure the systems adhere to that architecture.
• Stay up‑to‑date with emerging technologies and trends in LIMS engineering and ML Platform.

• Bachelor’s degree with 5 years of relevant experience or a Master’s degree with 3 years of relevant experience in computer science, life science, engineering, or a related field or equivalent training, fellowship, and/or work experience.
• Experience with ELN, LIMS, scientific data management, compound registration, sample inventory, instrument data capture, assay results, and electronic laboratory notebooks, such as CDD Vault and Dotmatics.
• A track record of achievements in designing and implementing LIMS apps for data access and/or visualization.
• Experience in evaluating, configuring, and tuning LIMS software for customized needs.
• Experience with administration, implementation, and integration of AI/ML and Data Lake Platform, such as Databricks.
• Applicable experience in software development and/or systems integration, preferably within a scientific or laboratory environment, especially one that is related to drug development.
• Experience with programming, scripting, and query languages and platforms like Python, Java, JavaScript, SQL.
• Experience with different types of data storage implementations, relational and non‑relational (e.g. key‑value, document, SQL, graph/graph databases), and optimizations of data storage by…