IA & Data Engineer M/F

pJoin AFD.
Tech, part of Accenture AFD.
Tech, part of Accenture, has established itself as a market leader by supporting major organizations in their digital transformation. As part of Accenture, a global consulting leader with more than 800,000 people worldwide, AFD.
Tech combines multisector expertise with the scale and capabilities of an international group. AFD.
Tech helps clients address today’s technology challenges and anticipate those of tomorrow. Its integration into Accenture in 2022 marked a key milestone in its growth, strengthening its presence and capabilities in strategic areas including networks, cloud and cybersecurity. /ph3Role overview /h3pWe are looking for a versatile Data Engineer / AI Engineer to design, build and maintain modern data platforms while contributing to the development and industrialization of Artificial Intelligence and Machine Learning solutions. You will work across different client environments and industries, collaborating with Data Scientists, Data Analysts, Software Engineers, Architects and business stakeholders. The ideal candidate combines strong Data Engineering fundamentals with practical exposure to AI, Machine Learning and Generative AI, and is comfortable working with modern cloud-based data ecosystems. /ph3Key responsibilities /h3ulliData Engineering Design, develop and maintain scalable data pipelines and ETL/ELT processes. /liliCollect, transform and integrate data from multiple structured and unstructured sources. /liliBuild and maintain data models and architectures supporting analytics and AI use cases. /liliEnsure data quality, reliability, performance and traceability. /liliDevelop batch and real-time data processing solutions. /liliOptimize data pipelines and processing workloads. /liliContribute to data platform architecture and technical design. /liliWork closely with Data Scientists and Data Analysts to provide reliable and accessible datasets. /liliAI Machine Learning Contribute to the development and deployment of Machine Learning and AI solutions. /liliPrepare and transform datasets for Machine Learning applications. /liliSupport the industrialization and deployment of ML models. /liliDevelop APIs or services to expose AI capabilities to applications. /liliContribute to Generative AI use cases, including LLM-based applications, RAG architectures, embeddings and vector databases. /liliImplement monitoring and continuous improvement mechanisms for AI solutions. /liliCollaborate with business stakeholders to translate concrete business challenges into Data AI solutions. /li /ulh3Technical skills /h3ulliData Engineering fundamentals Python SQL ETL / ELT pipelines Data modeling Data Warehousing and Data Lakes REST APIs and data integration /liliExperience with one or more of the following is highly valued:ulliDatabricks /liliApache Spark / PySpark /liliMicrosoft Fabric /liliSnowflake /liliApache Kafka /liliAirflow /lilidbt Cloud /li /ul /liliExperience with at least one major cloud ecosystem is required. Expertise across all three providers is not expected.ulliMicrosoft Azure: Azure Data Factory, Azure Data Lake Storage, Synapse Analytics and Azure Databricks. /liliAWS: S3, Glue, Lambda, Redshift and SageMaker. /liliGoogle Cloud Platform: BigQuery, Dataflow and Vertex AI. /li /ul /liliAI / Machine LearningulliMachine Learning concepts and algorithms. /liliPython data ecosystem: Pandas, NumPy and Scikit-learn. /liliML model deployment and APIs. /liliMLOps principles. /liliAzure Machine Learning, MLflow or equivalent tooling. /li /ul /liliExposure to Generative AI technologies is a strong asset:ulliLarge Language Models (LLMs). /liliRetrieval-Augmented Generation (RAG). /liliPrompt engineering. /liliEmbeddings and vector databases. /liliAzure OpenAI / OpenAI. /liliLangChain or similar frameworks. /li /ul /liliDevOps Software EngineeringulliGit and CI/CD pipelines. /liliDocker and Kubernetes. /liliInfrastructure as Code; Terraform is an asset. /liliAgile / Scrum delivery environments. /li /ul /li /ulh3Profile /h3ulli3+ years of experience in Data Engineering, AI/ML Engineering or a related role. /liliStrong proficiency in Python and SQL. /liliExperience building production-grade data pipelines. /liliExperience with cloud-based data platforms. /liliGood understanding of software engineering best practices. /liliStrong analytical and problem-solving skills. /liliAbility to communicate effectively with technical and non-technical stakeholders. /liliAutonomous, proactive and comfortable working in different client environments. /li /ulh3Nice to have /h3ulliExperience with Generative AI and LLM-based applications. /liliKnowledge of Data Governance and Data Quality principles. /liliExperience with real-time or event-driven architectures. /liliExperience delivering production Data/AI solutions within large organizations. /liliCloud or Data certifications such as Microsoft Azure, Databricks, AWS, Snowflake or Google Cloud certifications. /li /ulh3Language req