Elasticsearch Data Engineer – Medallion Architecture

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October 31

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Capgemini

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Enterprise • Artificial Intelligence • Cybersecurity

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.

10,000+ employees

Founded 1967

🏢 Enterprise

🤖 Artificial Intelligence

🔒 Cybersecurity

📋 Description

• **Our Client is one of the United States’ largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, our Client is part of one the largest Insurance Groups in the world.** • The Data Engineer will architect, develop, and maintain scalable data pipelines within a medallion architecture (bronze, silver/base vault, business vault, gold layers). This role is key in enabling high-quality, business-ready datasets by leveraging modern data engineering technologies and orchestration practices. • **Role Responsibilities:** • Design, build, and manage end-to-end data pipelines across the medallion architecture—specifically the bronze, silver (base vault with DBT and orchestration tools, business vault), and gold layers. • Ingest and process raw data using Spark and Amazon EMR for scalable, distributed computation. • Develop and automate data transformations for the base vault using DBT (Data Build Tool) to standardize and model data efficiently.

🎯 Requirements

• - At least 5 years of experience as an Elasticsearch Data Engineer - ELK (Elasticsearch, Logstash, and Kibana) stack Expert knowledge) • - Java Spring Boot • - IBM ACE Programming • - BS in Computer Science, Data Engineering (Big Data, AWS certification), Data Modeling or similar • - Full English Fluency • **Skills & Competencies** • - Strong understanding of data modeling, governance, and best practices in modern data architectures. • - Excellent analytical, problem-solving, and communication skills. • **Software / Tool Skills** • - **Elasticsearch** - cluster optimization, query development, data modeling, performance tuning & administration (4-6 Years) (**Must**) • - Deep experience with **Spark, Python and ETLs** and Amazon EMR (Must) • - Hands-on experience with **DBT** for data transformation and modeling. • - **Apache Airflow, AWS Step **Functions, or similar. (**Must**) • - Expert knowledge of **Amazon S3 and Apache Iceberg **for data storage and management. • - Experience with Kubernetes for container orchestration. • - Experience with Dremio, Looker, or equivalent business view/semantic layer technologies • - **AWS Cloud **– Intermediate, AWS **Lambda (Must) , Step Functions**, IAM, SNS, API Gateway, VPC, Transit Gateway, Intermediate (3-4 Years) • - **JSON** - Intermediate (4-6 Years) • - Jenkins – Data Pipeline Intermediate (4-6 Years) PLUS • - CloudWatch - Intermediate (4-6 Years) PLUS

🏖️ Benefits

• This position comes with competitive compensation and benefits package: • - Competitive salary and performance-based bonuses • - Comprehensive benefits package • - Career development and training opportunities • - Flexible work arrangements (remote and/or office-based) • - Dynamic and inclusive work culture within a globally renowned group • - Private Health Insurance • - Pension Plan • - Paid Time Off • - Training & Development