Data Engineer

Навыки

• Agile
• AI-инструменты в работе
• Airflow
• Самостоятельность
• Коммуникация
• Data Lake
• Data Quality

О компании и продукте

• Capgemini is a global business and technology transformation partner, helping organizations accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. It is a responsible and diverse organization with more than 340,000 team members in over 50 countries.
• With a strong heritage of more than 55 years, Capgemini helps clients unlock the value of technology through end-to-end services and solutions, leveraging capabilities in strategy and design, engineering, AI, generative AI, cloud, data, and digital transformation.
• At Capgemini Mexico, we are committed to fostering a diverse and inclusive workplace where everyone has equal opportunities. We welcome applications from all qualified candidates and evaluate them based on merit, skills, qualifications, and experience relevant to the role.

Задачи

• As a Senior Data Engineer at Capgemini , you will play a key role in a strategic data modernization initiative for a leading financial services organization
• You will help transform legacy data environments into modern, scalable data platforms by leveraging technologies such as Snowflake, Hive, Databricks, and Airflow
• This position requires a highly experienced and self-driven professional capable of rapidly understanding complex data ecosystems, optimizing data workflows, and delivering immediate value in a fast-paced environment with critical business impact
• Responsibilities & Scope
• Design, develop, and optimize scalable ETL and data processing pipelines
• Lead the migration of legacy SQL Server environments to modern cloud-based data platforms
• Develop, optimize, and maintain complex SQL queries for data transformation, reporting, and performance improvement
• Build, schedule, and maintain data workflows using Apache Airflow
• Design and develop data processing solutions using Python
• Create and optimize data models, including schema design, partitioning strategies, and performance tuning
• Analyze, troubleshoot, debug, and enhance existing data pipelines and integrations
• Ensure high levels of data quality, integrity, reliability, and governance across platforms
• Collaborate with data architects, analysts, business stakeholders, and engineering teams to deliver business-critical data solutions
• Identify bottlenecks, performance issues, and opportunities for improvement within complex data ecosystems
• Support the adoption of modern data engineering best practices and scalable architecture patterns
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Требования

• Results-driven professional – Capable of delivering value quickly in high-impact and fast-paced environments
• Strong analytical thinker – Experienced in solving complex data challenges and debugging sophisticated workflows
• Self-starter – Comfortable working independently with minimal supervision
• Problem solver – Able to investigate root causes and implement sustainable solutions
• Collaborative team player – Effectively partners with technical and business stakeholders
• Continuous learner – Passionate about modern data technologies and engineering best practices
• Qualifications & Preferred Skills
• 5+ years of experience in Data Engineering
• Advanced expertise in SQL with a strong focus on query optimization, data transformation, and performance tuning
• Proven experience designing and developing ETL and data processing solutions
• Strong ability to analyze, troubleshoot, and understand complex data pipelines and workflows
• Experience working independently and rapidly ramping up within new technical environments
• Strong understanding of data integration, data quality, and data lifecycle management
• Excellent analytical, problem-solving, and communication skills
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Будет плюсом

• Strong proficiency in Python for data engineering and automation tasks
• Experience building and maintaining workflows using Apache Airflow
• Exposure to Databricks and modern data lakehouse architectures
• Solid understanding of data warehousing concepts , dimensional modeling, and large-scale data processing
• Experience supporting cloud-based data platforms and modernization initiatives
• Familiarity with Agile methodologies and modern software development practices
• What You'll Love
• Opportunity to participate in a large-scale data modernization and transformation program
• Exposure to modern data technologies and enterprise-scale data platforms
• Access to industry-leading learning platforms, certifications, and professional development opportunities
• Collaborative, diverse, and innovative work environment
• Opportunities to work alongside highly skilled data and technology professionals globally
• Well-being initiatives and programs designed to support your personal and professional growth
• Need to Know
• Community Engagement: Participate in volunteering activities, technology communities, networking events, and knowledge-sharing sessions across Capgemini

Условия

• Career Development in Spanish & English: Access to training, certifications, mentorship programs, and learning opportunities designed to support your bilingual professional growth

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