We are seeking an experienced Data Engineer to design, develop, and maintain robust data pipelines and platforms. This role is crucial for enabling advanced analytics, reporting, and AI/ML initiatives. You will independently tackle complex data engineering challenges, collaborate with stakeholders to understand needs, and build reliable data solutions for the enterprise. As a technical mentor, you'll guide team members, share best practices, and drive continuous improvements in our data platforms and processes.

Key responsibilities include designing and building scalable data ingestion, transformation, and integration pipelines. You will develop and optimize ETL/ELT workflows for diverse data types and sources. Translating business requirements into effective technical data solutions and resolving complex engineering issues are core functions. Developing data models, ensuring data quality, and establishing validation processes are also essential. Collaboration with data analysts, scientists, and product teams to deliver trusted data assets is expected. Performance monitoring, optimization, and support for cloud-based data platforms are also part of this role. Implementing data governance, security, and compliance standards is vital. Creating technical documentation, participating in code reviews, and promoting engineering best practices are also key duties. Troubleshooting production issues, performing root-cause analysis, and contributing to automation and CI/CD are also expected.

A Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field is required. Candidates should possess 3+ years of experience in data engineering, software engineering, or big data development. Proven experience in developing ETL/ELT pipelines and working with large datasets is necessary. Familiarity with data warehouses, data lakes, and modern data architectures is essential. Strong proficiency in SQL and Python for data processing and engineering is a must. Knowledge of cloud platforms like Azure, AWS, or Google Cloud, along with an understanding of data modeling, quality, and governance principles, is required. Excellent analytical, problem-solving, communication, and stakeholder collaboration skills are vital. The ability to work independently and manage multiple priorities is also important.