Build the data backbone behind CONCELEX’s Data & AI transformation.You will design and operate the pipelines, lakehouse and data models that turn fragmented information into reliable data products. Working with sources ranging from ERP and accounting systems to SharePoint, legacy servers and historical documents, you will help create one trusted set of numbers for the business and a strong data foundation for AI applications.As one of the first engineers in a new Data & AI team, you will help shape the architecture, standards and ways of working for a platform built from the ground up.ResponsibilitiesDesign, build and operate ELT pipelines and a Bronze, Silver and Gold lakehouse.Integrate data from ERP and accounting systems, OneDrive, SharePoint, legacy servers and document archives.Develop dimensional models, business metrics and a Gold layer that supports finance, production and commercial reporting.Build orchestrated, tested and monitored workflows for batch and incremental data loads.Establish data quality checks, validation, lineage and reliable development and production practices.Work through complex legacy data, including inconsistent exports and undocumented sources.Prepare clean, well-modelled data for AI applications and retrieval use cases.Make efficient choices about storage, processing and orchestration to manage cloud costs.Collaborate with the Cloud Platform Engineer, Data Analyst and product stakeholders on infrastructure, metrics, data sources and adoption.Qualifications & ExperienceAround 7 years of data or software engineering experience, including ownership of production data platforms.Advanced SQL and solid Python skills.Strong experience with ELT, dimensional modelling and star schemas.Production experience with dbt or an equivalent transformation framework.Hands-on experience with Spark or equivalent distributed processing technology across batch and incremental workloads.Experience integrating messy legacy data, such as older ERP systems, Excel and CSV exports, and poorly documented files.Experience designing, operating and improving data solutions on a major cloud platform. Azure is preferred; strong AWS or GCP experience is also welcome.An AI-first working style, or enthusiasm for using AI development tools with sound engineering judgment.Nice to haveProduction orchestration experience with Airflow or a similar tool.Experience with data testing, quality monitoring and CI/CD.Knowledge of Databricks, Microsoft Fabric or Snowflake.Experience preparing data for LLM and RAG applications, including chunking, embeddings and retrieval quality.Power BI and semantic-layer modelling experience.Experience with streaming or event pipelines, such as Kafka.Basic Infrastructure as Code experience with Terraform or a similar tool.ERP data experience in finance, projects, construction or another asset-intensive industry. Show more Show less