Join our dynamic team as a Data Engineer, focusing on building and maintaining robust data pipelines and platforms that power analytics, reporting, and AI/ML initiatives. This role offers the opportunity to tackle moderately complex data engineering challenges independently and collaborate with key stakeholders to deliver impactful data solutions. You'll also serve as a technical mentor to your colleagues, contributing to the ongoing enhancement of our data infrastructure and engineering practices.

Key responsibilities include designing, developing, and maintaining scalable data ingestion, transformation, and integration pipelines. You will build and optimize ETL/ELT workflows, process diverse data types from multiple sources, and translate business requirements into effective technical data solutions. Identifying and resolving intricate data challenges, developing data models, and establishing data quality frameworks are also crucial. Collaboration with analysts, scientists, and product teams to deliver trusted data assets, alongside monitoring and optimizing pipeline performance, reliability, and cost efficiency, are essential functions. Support for cloud-based data platforms, data warehouses, and lakehouses, while implementing data governance, security, and compliance standards, will be integral to the role. Creating technical documentation and promoting engineering best practices through code reviews and CI/CD processes are also expected. Troubleshooting production issues, performing root-cause analysis, and contributing to continuous improvement initiatives will round out your contributions.

We are seeking candidates with a Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a closely related field. A minimum of 3 years of experience in data engineering, software engineering, or big data development is required. Proficiency in developing ETL/ELT pipelines, working with large-scale datasets, and experience with data warehouses, data lakes, and modern data architectures are essential. Strong skills in SQL and Python for data processing and engineering are a must, along with knowledge of cloud platforms like Azure, AWS, or Google Cloud. A solid understanding of data modeling, data quality, and data governance principles is expected. The ideal candidate will possess proven analytical and problem-solving skills, excellent communication and stakeholder collaboration abilities, and the capacity to work independently on multiple priorities with minimal supervision.