Data Engineer (Spanish)

AXA Global Business Services is a subsidiary of AXA Group, one of the leading insurance brands in the world. We embody the essence of a diverse, global team, uniting talents from around the world to create a seamless, supportive network for all AXA entities. Our story is one of collaboration and growth, deeply rooted in our mission and vision, guiding every step we take. Our Mission: Together with entities, we deliver advanced services and shape solutions that drive operational excellence. In the heart of AXA, our role is multi-layered. From insurance operations to corporate functions, we leverage data, technology, and diverse capabilities to enhance our partners' performance in a streamlined, efficient manner. Our Vision: Building on unique capabilities and expertise, our teams dare to open new doors for AXA. We are not just about today; we are shaping tomorrow. Our vision is to continuously develop new skills and solutions, opening doors to fresh opportunities. This means committing to the highest service and quality levels, embracing continuous improvement, and fostering courage and boldness within our team. For over 25 years, our operations have spanned across five delivery centres in India and Morocco, serving more than 35 AXA entities. Our 3,800+ strong workforce is the heartbeat of our organisation, moving forward in a culture of trust, empowerment, and care. Driven by our values, we are a cohesive global team, quick to adapt to market dynamics, united by the desire to excel. Our Centres of Excellence (COEs) offer advanced services, shaping tailor-made solutions for our partners in the Tech, Security, Data, Insurance Ops and Corporate function Ops domain. The AXAllence strategic plan for 2024-26 charts our future course, focusing on operational efficiency, employee retention and skill enhancement, and delivering unparalleled value to our partners. These pillars, supported by our vision and mission, are the foundation of our commitment to AXA. In essence, while our heritage lies in delivering value in BPO services, our innovative spirit thrives in the IT domain, all in support of the overarching AXA Group strategy. At AXA Global Business Services, we are not just preparing for the future; we are actively creating it. At AXA Global Business Services, the future is brimming with opportunities. Join us on this exciting journey! Together, we will continue to open new doors for AXA. JOB PURPOSE We are looking for a technically proficient Data Engineer (Databricks) to design, build, and maintain scalable data platforms supporting business and analytics needs across multiple domains. You will be responsible for developing robust data pipelines, integrating multiple data sources, ensuring data quality and governance, and contributing to the continuous improvement of the Data & Analytics ecosystem. This role requires strong expertise in data engineering, cloud technologies, problem-solving capabilities, and the ability to collaborate effectively with business and technical teams. PROFILE As a Data Engineer, you support business and analytics teams by designing and implementing data solutions, developing and optimizing data pipelines, and ensuring the availability, quality, and reliability of enterprise data assets. You contribute to delivering scalable, secure, and high-performance data platforms while ensuring compliance with data governance standards, security requirements, and engineering best practices. RESPONSIBILITIES • Analyze business and technical requirements and translate them into scalable data engineering solutions. • Design, develop, test, and maintain batch and streaming data pipelines. • Build and optimize ETL/ELT processes using Databricks and PySpark. • Develop and maintain data lake and data warehouse architectures on Azure and/or AWS. • Integrate data from multiple internal and external sources. • Monitor and improve data quality, reliability, and performance. • Implement data governance, security, and access management best practices. • Collaborate with Data Analysts, Data Scientists, AI Engineers, and business stakeholders. • Support deployment activities, automation initiatives, and CI/CD implementation. • Produce technical documentation and share knowledge with team members. • Contribute to the continuous improvement of data engineering standards, frameworks, and processes. TECHNICAL SKILLS Data Engineering & Data Processing • Strong expertise in Data Engineering concepts and best practices. • Experience designing and operating large-scale data pipelines. • Strong knowledge of batch and streaming data processing architectures. • Experience handling structured, semi-structured, and unstructured data. • Understanding of distributed computing concepts and big data ecosystems. Databricks & PySpark • Strong hands-on experience with Databricks. • Excellent knowledge of PySpark for data transformation and processing. • Experience optimizing Spark jobs and cluster performance. • Knowledge of Delta Lake and Lakehouse architectures. • Experience implementing scalable and reliable data workloads within Databricks environments. Cloud Platforms • Experience with Azure Data Services and/or AWS Data Stack. • Good understanding of cloud-native data architectures. • Experience working with cloud storage and compute services. • Knowledge of cloud security and governance principles. • Experience deploying and managing data solutions in cloud environments. SQL & Data Modeling • Strong SQL skills for data extraction, transformation, and validation. • Experience designing and maintaining data warehouse solutions. • Knowledge of dimensional modeling concepts including Star and Snowflake schemas. • Understanding of data integration and data migration practices. • Experience optimizing database and query performance. Data Quality, Security & Governance • Strong understanding of data quality frameworks and monitoring practices. • Experience implementing data governance policies and standards. • Knowledge of data lineage, metadata management, and cataloging principles. • Understanding of data privacy, security, and compliance requirements. • Ability to troubleshoot and resolve data issues effectively. DevOps & Automation • Experience with CI/CD pipelines and deployment automation. • Understanding of source control and collaborative development practices. • Familiarity with Git and version control workflows. • Knowledge of Infrastructure as Code concepts is considered an asset. • Experience with Azure DevOps or similar tools would be considered an advantage. SOFTWARE & TECHNICAL ENVIRONMENT • Python • PySpark • SQL • Databricks • Delta Lake • Azure Data Factory • Azure Data Lake Storage • Azure Synapse Analytics (asset) • AWS Data Services (S3, Glue, Redshift, EMR) • Git • Azure DevOps • CI/CD Frameworks • Data Warehouse & Lakehouse Architectures PROFESSIONAL SKILLS • Excellent communication and interpersonal skills. • Ability to interact effectively with business and technical stakeholders. • Strong analytical and problem-solving skills. • Strong data-oriented mindset and attention to detail. • Customer-oriented mindset and service excellence approach. • Ability to work autonomously while maintaining strong collaboration within teams. • Curiosity and willingness to learn new technologies and cloud services. • Ability to work in multi-site and cross-functional environments. • Strong commitment to quality, reliability, and continuous improvement. EXPERIENCE & DELIVERABLES • 2 to 7 years of experience in Data Engineering and cloud data platforms. • Proven experience developing and maintaining data pipelines using Databricks and PySpark. • Understanding of ETL/ELT processes and data pipeline development. • Strong autonomy in delivering data integration and transformation projects. • Significant experience designing large-scale data architectures and enterprise data solutions. • Experience leading complex data transformation and modernization initiatives. Common Requirements • Strong experience with Python, PySpark, and SQL. • Experience with Databricks and Azure Data Services and/or AWS data stack. • Experience working in Agile environments. • Ability to produce technical documentation and knowledge-transfer materials. • Experience participating in the complete project lifecycle, from requirements gathering to production deployment. • Databricks, Azure, AWS, or related cloud certifications would be considered a strong advantage. • Spanish mandatory (professional level), French and/or English preferred.