Advance your career as a Data Engineer focused on building and maintaining robust data pipelines and platforms. This role is central to enabling analytics, reporting, and AI/ML initiatives by creating scalable data solutions.

You will tackle moderately complex data engineering challenges independently, collaborating closely with business and technology partners to translate requirements into reliable data assets. As a key technical resource, you will guide team members on best practices and drive continuous improvement of our data platforms and engineering processes.

Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines. Build and optimize ETL/ELT workflows for diverse data sources. Analyze requirements and translate them into effective technical data solutions. Address and resolve non-standard data challenges and complex engineering problems. Develop and maintain data models, quality frameworks, and validation processes. Collaborate with stakeholders to deliver trusted data assets. Monitor and optimize pipeline performance, reliability, scalability, and cost. Support cloud-based data platforms and data warehouse/lakehouse environments. Implement data governance, security, lineage, and compliance standards. Create comprehensive technical documentation and operational procedures. Participate in code reviews and uphold engineering best practices. Troubleshoot production issues and implement sustainable solutions. Contribute to automation, CI/CD, and continuous improvement initiatives. Adhere to company policies and employment contract terms.

A Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field is required. A minimum of 3 years of experience in data engineering, software engineering, or big data development. Proven experience developing ETL/ELT pipelines and working with large-scale datasets. Familiarity with data warehouses, data lakes, and modern data architectures. Solid proficiency in SQL and Python for data processing and engineering. Understanding of cloud-based data platforms like Azure, AWS, or Google Cloud. Knowledge of data modeling, data quality, and data governance principles. Demonstrated analytical and problem-solving skills. Excellent communication and stakeholder collaboration abilities. Ability to work independently and manage multiple priorities effectively.