Data Engineer

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August 22

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Thaloz

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SaaS • B2B • Enterprise

Thaloz is a tech consulting and outsourcing company focused on cloud-native product development and engineering team outsourcing. They offer tailored software development solutions, leveraging top-tier talent from Latin America. Thaloz provides a variety of services such as custom product development, staff augmentation, and enterprise solutions. Their approach emphasizes people-focused consulting and remote work culture, ensuring seamless integration of skilled IT professionals into their clients' projects. With expertise in diverse technologies, Thaloz offers end-to-end support from strategy to launch, fostering smooth communication and collaboration.

51 - 200 employees

☁️ SaaS

🤝 B2B

🏢 Enterprise

📋 Description

• Senior Data Engineer responsible for designing, building, and maintaining scalable and reliable data pipelines and ETL processes for the Credit Platform Data team. • Architect, develop, and maintain scalable data pipelines and ETL workflows that support the ingestion, transformation, and storage of large datasets from diverse sources. • Implement automated data quality checks and validation processes to ensure the accuracy, consistency, and reliability of data across systems. • Work closely with product managers, data analysts, and business stakeholders to gather and understand data requirements, translating them into technical specifications and actionable engineering tasks. • Continuously monitor and optimize data systems for performance, scalability, and cost-efficiency, ensuring that data infrastructure meets evolving business needs. • Diagnose and resolve data-related issues promptly, providing root cause analysis and implementing preventive measures. • Maintain comprehensive documentation of data pipelines, ETL processes, and system architecture. Participate in design and code reviews to uphold high engineering standards. • Stay abreast of emerging data engineering technologies, tools, and best practices to drive innovation and continuous improvement within the team. • Provide guidance and mentorship to junior data engineers, fostering a culture of knowledge sharing and technical excellence.

🎯 Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field. • SQL: Expert-level proficiency in SQL for querying, manipulating, and optimizing relational databases. Ability to write complex queries, optimize performance, and work with large datasets efficiently. • Python: Strong programming skills in Python, including experience with data processing libraries such as Pandas. Ability to develop robust, maintainable, and scalable data processing scripts and automation tools. • PySpark: Proficient in using PySpark for distributed data processing on large-scale datasets. Experience with Spark's DataFrame API, RDDs, and performance tuning in a big data environment. • ETL (Extract, Transform, Load): Deep understanding of ETL concepts and hands-on experience designing and implementing ETL pipelines that ensure data integrity and efficiency. • Data Modeling: Expertise in data modeling techniques to design logical and physical data models that support efficient querying and reporting. Familiarity with normalization, denormalization, and schema design best practices. • Relational Databases: Experience working with relational database management systems (RDBMS) such as Oracle, MySQL, or similar platforms. Knowledge of database design, indexing, and query optimization. • Data Warehousing: Solid understanding of data warehousing concepts, architectures, and best practices. Experience building and maintaining data warehouses that support business intelligence and analytics. • Unix/Linux: Proficiency in Unix/Linux operating systems for managing data workflows, scripting, and system monitoring. • Shell Scripting: Ability to write shell scripts to automate routine tasks, manage data pipelines, and integrate with other system components. • Automation Testing: Experience implementing automated testing frameworks for data pipelines and ETL processes to ensure data quality and system reliability. • Professional Experience: Minimum of 3+ years of proven experience as a Data Engineer or in a similar role, with a strong background in database development, ETL processes, and software development.