Senior Data Lead Engineer

Company Description Why Talan? Talan – Positive Innovation Talan is an international consulting group specializing in innovation and business transformation through technology. With over 7,200 consultants in 21 countries and a turnover of €850M, we are committed to delivering impactful, future-ready solutions. Talan at a Glance Headquartered in Paris and operating globally, Talan combines technology, innovation, and empowerment to deliver measurable results for our clients. Over the past 22 years, we’ve built a strong presence in the IT and consulting landscape, and we’re on track to reach €1 billion in revenue this year. Our Core Areas of Expertise Data & Technologies: We design and implement large-scale, end-to-end architecture and data solutions, including data integration, data science, visualization, Big Data, AI, and Generative AI. Cloud & Application Services: We integrate leading platforms such as SAP, Salesforce, Oracle, Microsoft, AWS, and IBM Maximo, helping clients transition to the cloud and improve operational efficiency. Management & Innovation Consulting: We lead business and digital transformation initiatives through project and change management best practices (PM, PMO, Agile, Scrum, Product Ownership), and support domains such as Supply Chain, Cybersecurity, and ESG/Low-Carbon strategies. We work with major global clients across diverse sectors, including Transport & Logistics, Financial Services, Energy & Utilities, Retail, and Media & Telecommunications. Job Description As a Senior Data Lead Engineer , your mission will be to lead the design, evolution and operation of cloud-based Data, AI & BI platforms , enabling scalable, secure and high-quality data products that drive business value. You will play a key role in defining the data roadmap, mentoring engineering teams and delivering advanced analytics and AI use cases in a complex and large-scale environment. We need someone like you to contribute across the following responsibilities: Lead the Data, AI & BI roadmap , ensuring scalability, resilience, security and cost efficiency. Design, evolve and operate cloud data lakehouse architectures . Define and build domain-oriented data products aligned with data mesh principles (data-as-a-product, SLAs, ownership). Build and maintain data ingestion, ETL and transformation pipelines , including CDC-based and event-driven architectures. Integrate cloud platforms with on-premise data platforms in hybrid environments. Implement and enforce data governance, data quality rules and data guardrails . Deliver high-quality, well-modelled datasets and semantic layers for BI, reporting and analytics. Enable AI/ML and LLM use cases (feature engineering, training, RAG, fine-tuning, monitoring). Promote engineering best practices and act as a technical leader and mentor for data, ML and BI engineers. Collaborate with product, technology and business teams to prioritise and deliver high-impact initiatives. Qualifications EXPERIENCE 5+ years of experience in Data Engineering, Data Platforms, AI Engineering or Advanced Analytics . Proven experience designing and building cloud data platforms and lakehouse architectures (preferably AWS). Hands-on experience with Databricks or EMR for large-scale data processing. Strong background in data ingestion, ETL and CDC-based pipelines . Experience working with hybrid architectures (on-premise + cloud). Experience enabling AI/ML solutions in production . Experience collaborating with BI teams and business stakeholders on data modelling and KPI definition. EDUCATION Bachelor’s degree or higher in Computer Science, Engineering, Mathematics or a related technical discipline. Additional training in Data Engineering, AI/ML or Analytics is a plus. SKILLS & KNOWLEDGE AWS: S3, Lake Formation, Glue, EMR. Databricks: Spark (PySpark/Scala), Delta tables, MLflow, feature store, performance optimisation. Strong SQL and Python skills for data processing and automation. Data formats and lakehouse concepts: Parquet, Iceberg / Delta , curated layers. Experience with data quality, lineage, observability and monitoring . Knowledge of CDC patterns and event-driven ingestion. Understanding of data mesh principles and federated governance. Experience supporting ML workflows (feature engineering, training, deployment, monitoring). Knowledge of LLMs (prompt engineering, fine-tuning, RAG, evaluation and guardrails). Strong understanding of BI concepts , semantic modelling and analytics consumption. Practical experience with data governance, data rules and data guardrails . SOFT SKILLS Strong communication skills, able to explain complex data and AI topics to technical and non-technical audiences. Ability to influence and align multiple teams without direct authority. Proven leadership and mentoring capabilities. Proactive, hands-on and outcome-oriented mindset. Collaborative and adaptable in complex environments. OTHER INFORMATION / NICE TO H ``` (Note: The JSON string above continues with the rest of the formatted description as written in the analysis. Please ensure the final output includes the complete sanitized HTML as shown, without any additional tags or formatting beyond the allowed set.) #J-18808-Ljbffr