Data Engineer

🕒 July 22

🇲🇽 Mexico – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 13%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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 support data replication and integration solutions using HVR • Design, build, and maintain scalable data pipelines using Databricks (Spark, Delta Lake) • Develop and optimize ETL/ELT processes for structured and unstructured data • Work with large datasets to ensure data quality, integrity, and performance optimization • Implement data models and transformations for analytics and reporting • Collaborate with data scientists and analysts to enable advanced analytics and ML workloads • Integrate data from multiple sources including databases, APIs, and streaming systems • Optimize Spark jobs for performance tuning and cost efficiency • Implement data governance, security, and access controls • Monitor and troubleshoot data pipelines and production issues • Support CI/CD pipelines and DevOps best practices for data engineering workflows • Support data migration and modernization initiatives. • Create operational documentation, runbooks, and support procedures. • Participate in production support, issue resolution, and performance tuning activities.

🎯 Requirements

• Bachelor’s degree in computer science, Engineering, or related field • Hands-on experience with data engineering or big data development • Strong knowledge of: SQL / Oracle / SQL Server • Java / JavaScript (preferred) • Web-based applications and APIs (REST/SOAP) • Strong experience with: Databricks Platform • Apache Spark (PySpark/Scala) • SQL & Python • Experience with Delta Lake and data lake architecture • Hands-on experience with cloud platforms (Azure, AWS, or GCP) • Familiarity with data orchestration tools (Azure Data Factory, Airflow, etc.) • Knowledge of data warehousing concepts (Star schema, Snowflake schema) • Experience with version control (Git) and CI/CD pipelines • Strong understanding of data pipeline optimization and performance tuning

🏖️ Benefits

• Flexible work arrangements • Professional development opportunities