Data Engineer Manager

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🔥 12 hours ago

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qode.world

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

👥 HR Tech

🎯 Recruiter

Artificial Intelligence • HR Tech • Recruitment

qode. world is a company that leverages artificial intelligence to revolutionize the recruiting process. Their platform allows users to find candidates by sourcing data from billions of data points worldwide and provides data-driven insights. Users can connect with candidates directly through the platform, conduct customized AI-led interviews, and get comprehensive assessments. The service also integrates easily with LinkedIn, enhancing the talent pool and facilitating direct communication with candidates listed there. Qode. world offers additional recruiting services to assist in hiring for niche or senior roles. They are praised for their effectiveness in streamlining the hiring process and delivering quick results.

📋 Description

• Design and implement robust, scalable data pipelines for structured and unstructured data. • Oversee ETL/ELT processes to ingest data from core banking systems, CRM, and external sources. • Ensure data models support real-time analytics, reporting, and machine learning. • Collaborate with data scientists and analysts to provide usable, cleaned and aggregated data to end users • Ensure data practices comply with banking regulations (e.g., Basel III, GDPR, local laws). • Implement data governance frameworks, including metadata management and lineage tracking. • Collaborate with cybersecurity teams to safeguard sensitive financial data. • Monitor and optimize data infrastructure for performance, reliability, and cost-efficiency. • Troubleshoot data issues and ensure high availability of data services. • Evaluate and adopt modern data technologies (e.g., cloud platforms, data lakes, streaming tools). • Promote automation and DevOps practices in data engineering workflows.

🎯 Requirements

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field. • At least 7 years in data engineering, with 2+ years in a leadership role. • Strong experience with SQL, Python/Scala, Spark, Kafka, and cloud platforms (AWS/GCP/Azure). • Familiarity with banking systems, financial data structures, and regulatory requirements. • Excellent communication and stakeholder management skills.