Data Engineer – Databricks

🕒 October 27

🇲🇽 Mexico – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 18%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Open for 17 days.
• Jobs at this company usually fill in 217 days.
• No salary listed.

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Capgemini

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1967

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Capgemini is a global leader in partnering with businesses to transform and manage their operations by harnessing the power of technology. With expertise across a wide array of industries such as aerospace, automotive, banking, and healthcare, Capgemini provides a constantly evolving portfolio of services to meet the ever-changing needs of their clients. Their offerings include cloud, cybersecurity, data and artificial intelligence, and enterprise management, among others. Capgemini also emphasizes innovation and sustainability, helping companies achieve digital transformation while promoting environmental and social responsibility. Additionally, Capgemini provides career opportunities across various levels and professions, encouraging innovation and diversity in its workforce.

📋 Description

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python and Databricks • Develop data processing and transformation solutions using Spark and PySpark • Build, optimize, and maintain Databricks notebooks, workflows, and jobs • Integrate data from databases, APIs, files, and cloud storage • Perform data cleansing, enrichment, and validation activities • Optimize data pipelines and Spark workloads for performance, scalability, reliability, monitoring, logging, and troubleshooting • Collaborate with analysts, developers, architects, and business teams • Participate in code reviews, testing, documentation, CI/CD, and production support activities

🎯 Requirements

• Strong hands-on experience with Python, Databricks, Apache Spark, and PySpark • Experience building and supporting production-grade ETL/ELT data pipelines • Strong SQL skills • Experience with data modeling, data transformation, and data quality practices • Experience working with Delta Lake and Lakehouse architectures • Experience integrating data from databases, APIs, files, and cloud storage • Understanding of Git, CI/CD, testing, and engineering best practices

🏖️ Benefits

• Work on meaningful projects that use technology to solve real-world challenges • Access continuous learning through internal academies, certifications, and mentorship • Professional communities to connect with and support career growth • Remote work model • Access to Capgemini offices in Mexico City, Aguascalientes, and Guadalajara for collaboration and team interactions when needed

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