Expert Data Engineer, Research, Innovation & Labs
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Job description
ppExpert Data Engineer, Research, Innovation Labs - Barcelona, Spain /p pJoin us as an Expert Data Engineer to design and maintain robust data pipelines, ensuring seamless data integration and transformation.Collaborate with data modelers, scientists, and business partners to drive impactful projects centered around our data.Elevate your career by mastering cutting-edge tools and technologies in a dynamic, innovative environment./p h3Key Responsibilities /h3 ul liProvide technical recommendations and evaluate project feasibility and workloads./li liDesign and implement efficient pipeline architectures for data ingestion, transformation, and storage./li liDevelop modular, efficient code for data transformation and integration, ensuring adherence to modern development practices./li liPerform data ingestion from source systems, including ETL processes, when tables are not available on the data platform.Conduct regular pipeline maintenance and upgrades, troubleshooting and resolving issues to ensure optimal performance./li liImplement data quality testing and validation to maintain high standards of data integrity and reliability./li liCollaborate closely with other data engineers, data modelers, data stewards, BI developers, data scientists, and subject matter experts to ensure seamless data integration, knowledge sharing, and delivery of impactful solutions./li /ul h3Benefits Opportunities /h3 ul liUnique career paths across health, nutrition and beauty; explore what drives you and get the support to make it happen./li liA chance to impact millions of consumers every day, sustainability embedded in all we do./li liA science?led company with cutting?edge research and creativity; work on what's next./li liGrowth opportunities with an industry leader that supports expertise and leadership development./li liA culture that lifts you up with collaborative teams, shared wins, and people who cheer each other on./li liA community where your voice matters to serve customers well./li /ul h3Qualifications /h3 ul liExpert knowledge in dbt, SQL, Python, Spark, Cypher, Git, and Databricks./li liExpertise in cloud engineering (e.g., AWS, Azure), infra?as?code, and deploying CICD pipelines is a plus./li liExperience with graph databases (e.g., Neo4j), integrating with both commercial and custom?built scientific software applications is a plus./li liStrong problem?solving skills./li li3+ years of experience creating and maintaining data pipelines within the science, innovation, and labs domain for health, nutrition and beauty./li liExperience handling scientific datasets for cheminformatics or bioinformatics (e.g., microbiome) is a plus./li liExperience with FAIR data principles, data governance and data standards used in the scientific domain./li liAbility to collaborate closely with data experts and subject matter experts to ensure seamless data integration and transformation./li liConsistently use best practices in coding, testing, and documentation to deliver scalable data solutions, ensuring accuracy and reliability through automated quality checks and monitoring tools./li liCuriosity and an open mind: relentlessly ask "Is there a better way?" to leverage data for smarter decision?making./li /ul h3Inclusion Equal Opportunity /h3 pWe're proud to be an equal opportunity employer.We welcome candidates from all backgrounds-no matter your gender, ethnicity, sexual orientation, or anything else that makes you, you.If you have a disability or need support during the application process, we're here to help./p /p #J-*****-Ljbffr
Requirements
li /ul h3Qualifications /h3 ul liExpert knowledge in dbt, SQL, Python, Spark, Cypher, Git, and Databricks. /li liExpertise in cloud engineering (e.g., AWS, Azure), infra?as?code, and deploying CICD pipelines is a plus. /li liExperience with graph databases (e.g., Neo4j), integrating with both commercial and custom?built scientific software applications is a plus. /li liStrong problem?solving skills. /li li3+ years of experience creating and maintaining data pipelines within the science, innovation, and labs domain for health, nutrition and beauty. /li liExperience handling scientific datasets for cheminformatics or bioinformatics (e.g., microbiome) is a plus.