Big Data Developer

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October 24

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First Technology

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Enterprise • SaaS • Cybersecurity

First Technology is a leading IT integration group in the EMEA region, providing comprehensive technology solutions to meet real business challenges. They specialize in hybrid data center and cloud services, modern workplace solutions, cybersecurity, managed services, and professional services. With a focus on maximizing productivity, optimizing security, modernizing workplaces, and controlling costs, First Technology is committed to delivering cutting-edge solutions that empower businesses to thrive in a changing technological landscape. Their expertise extends to artificial intelligence, where they incorporate AI into business solutions responsibly and securely. They are also a Microsoft partner, offering specialized services in Microsoft technologies.

1001 - 5000 employees

Founded 1983

🏢 Enterprise

☁️ SaaS

🔒 Cybersecurity

📋 Description

• Analyze, refactor, and modernize Spark/MapReduce/Hive/Tez jobs for execution within NexusOne’s managed Spark and Trino environments. • Design, build, and optimize batch and streaming pipelines using Spark, NiFi, and Kafka. • Convert existing ETL jobs and DAGs from Cloudera/MAPR ecosystems to open-source equivalents. • Collaborate with Data Engineers and Architects to define new data ingestion and transformation patterns. • Tune performance across large-scale data processing workloads (partitioning, caching, resource allocation). • Implement data quality and validation frameworks to ensure consistency during migration. • Support code reviews, performance tests, and production readiness validation for migrated workloads. • Document conversion approaches, dependencies, and operational runbooks. • Partner with Wells Fargo application SMEs to ensure domain alignment and business continuity.

🎯 Requirements

• 4–8 years of experience in big data engineering or application modernization in enterprise settings. • Prior experience with Cloudera, MAPR, or Hadoop ecosystems, transitioning to open-source frameworks. • Strong understanding of distributed data architectures and data lake design principles. • Exposure to hybrid or cloud-native environments (AWS, GCP, or Azure). • Familiarity with regulated environments (financial services, telecom, healthcare) is a plus.