Location: Stone, Staffordshire (Hybrid working, 2 days in our Stone office) Status: Permanent, Full Time Package: Competitive Salary, Flexible Working (with one-off allowance and 2 Days in the office), Development & Opportunity (Personal & Technical), Private Medical (Optical & Dental options), Matching Contributory Pension, 25 Days Leave Public Holidays Buy and Sell Scheme, Life Insurance, Referral Scheme, Employee Assistance Program, Benefits Hub. Who’s Instem? Well, we’re a global provider of bespoke industry-leading software solutions and services, which facilitate the pre-clinical, and clinical phases of the drug discovery process. We have over fifteen products in our portfolio, used by over 700 pharmaceutical clients (including all the top 20!) What’s the culture/environment like? For a global business of over 300 staff, we very much have a family feel. You’ll be part of a friendly, communal, solution based, flexible environment, where you’ll feel empowered, valued and accountable. We’ll invest in you as a person and encourage you to take part in companywide workshops for wellbeing, mental health, critical conversations, and strengths. Why are we hiring a Data Engineer? This is a newly created role and it will be critical to ensuring that data is accessible, reliable, and optimized for analytics and business intelligence across the organization. What are you responsible for? Data Ingestion & Integration Design and implement robust data pipelines to ingest data from multiple internal and external sources (e.g., databases, APIs, flat files, cloud services). Develop ETL/ELT processes to clean, transform, and prepare data for analysis. Integrate structured and unstructured data from disparate systems. Data Modelling & Storage Design scalable and performant data models (star/snowflake schemas, normalized/denormalized structures) for analytical workloads. Build and maintain data warehouses, data lakes, or Lakehouse architectures. Define metadata, data lineage, and schema management processes. Data Quality & Governance Implement validation and profiling routines to monitor data quality and consistency. Set up logging, alerting, and metrics for pipeline reliability and data integrity. Collaborate with data stewards and governance teams to align with data standards. Collaboration and Exploration Work with data scientists, analysts, and domain experts to understand data requirements and research use cases. Prototype data sets and transformation logic to support exploration and discovery. Help define and prioritize data needs based on early-stage research opportunity signals. Infrastructure & Automation Automate data workflows using orchestration tools (e.g., Airflow, Prefect). Contribute to the deployment of cloud-native or hybrid data infrastructure. Optimize pipeline performance and cost efficiency (e.g., storage, compute). Strategic Input Identify gaps in current data availability or quality that may block research opportunity detection. Recommend tools, platforms, or architectural patterns to enhance data capabilities. Contribute to a roadmap for data engineering and analytics maturity. Adherence to the Company’s Quality Management System to ensure that all work is handled Securely, Professionally and Diligently Skills, Knowledge And Experience Technical Skills Programming – proficiency in Python, SQL, and optionally Scala or Java. Data Platforms – experience with cloud-based data services (e.g., AWS Redshift, Azure Synapse, GCP BigQuery, Snowflake). ETL Tools – Airflow, dbt, Apache NiFi, or similar tools for workflow and pipeline orchestration. Data Storage – familiarity with relational databases (PostgreSQL, MySQL), NoSQL (MongoDB, DynamoDB), and file formats (Parquet, Avro, JSON). Data Modelling – strong grasp of dimensional modelling and data warehousing concepts. DevOps/DataOps – Git, CI/CD pipelines, infrastructure as code (Terraform, CloudFormation). Knowledge Areas Data Architecture – understanding of modern data architecture patterns (e.g., medallion architecture, data mesh, lambda architecture). Data Governance – awareness of data privacy, security, and compliance (e.g., GDPR, HIPAA). Analytics Foundations – understanding of how data is used for analysis, ML, or research, even if not directly building models. Experience Hands-on experience as a data engineer or in a similar role. Experience working in cross-functional teams, ideally in research-heavy or data-driven environments (e.g., life sciences, pharma, healthcare, academia). Knowledge of chemical structure representation, nomenclature, chemical transformation, and structure activity relationship forms Knowledge of toxicology and toxicological study types Proven ability to work independently on open-ended tasks, including shaping requirements and driving toward implementation. Experience with exploratory data work, helping uncover patterns or opportunities through early-stage prototyping. Knowledge of our Quality Management System and its application to tasks associated with this role An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability. Instem stores and processes data using an Applicant Tracking System (ATS). For more information regarding our privacy policy use the following link: http://www.instem.com/about/data-protection.php