Data Engineer I

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August 12

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Prioclen Holdings

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Fintech • SaaS • Energy

Prioclen Holdings is a diversified holding company operating subsidiaries across consulting, technology, capital, data and energy. The group builds data-driven product and cloud solutions to connect data and empower decision-making, with a specific focus on establishing data infrastructure to improve consumer accessibility and affordability of financial services in emerging markets. Other subsidiaries provide consulting, capital management and energy services, positioning the company as an innovation-driven, sustainability-minded operator in multiple sectors.

11 - 50 employees

Founded 2024

💳 Fintech

☁️ SaaS

⚡ Energy

📋 Description

• Design, develop, and maintain data pipelines and ETL processes using Python and tools like Azure Data Factory. • Collaborate with data scientists to train, validate, and deploy machine learning models. • Ingest, clean, and transform data from structured and unstructured sources into well-organized datasets. • Monitor data pipelines for quality, reliability, and performance, implementing improvements where necessary. • Ensure compliance with security standards and data governance policies. • Participate in troubleshooting data issues, performing root cause analysis, and applying fixes. • Maintain clear documentation for data workflows, schemas, and ML processes. • Continuously explore and evaluate new tools and frameworks to improve data engineering and ML operations.

🎯 Requirements

• Proficiency in Python for data processing, pipeline development, and machine learning workflows. • Familiarity with Azure Data Factory or similar orchestration tools. • Basic understanding of machine learning principles and practical experience in model training. • Working knowledge of SQL and database design. • Awareness of security, privacy, and compliance considerations in data handling. • Strong problem-solving skills with a detail-oriented approach. • Ability to work collaboratively in a cross-functional environment.

🏖️ Benefits

• Opportunities to grow into advanced data engineering, ML engineering, or data architecture roles. • A collaborative environment that values curiosity, learning, and experimentation. • Competitive compensation and benefits package. • Leave & Time Off — Colleagues are entitled to up to 20 days of leave excluding public holidays , 11 sick leave days , and 4 days quarterly for skill development as per company policy.