Join our dynamic team as a Data Engineer, focusing on building and maintaining scalable data solutions. This role is crucial for enabling advanced analytics, reporting, and AI/ML initiatives. You will independently tackle moderately complex data engineering challenges and collaborate closely with business and technology stakeholders.

As a technical expert, you'll offer guidance to team members, champion best practices, and actively contribute to enhancing our data platforms and engineering processes. This is an excellent opportunity to make a significant impact on enterprise-wide data needs.

Key responsibilities include designing, developing, and maintaining robust data ingestion, transformation, and integration pipelines. You will build and optimize ETL/ELT workflows for diverse data types and sources, translating business requirements into effective technical data solutions.

Problem-solving for non-standard data challenges and complex engineering issues will be a core part of your role. You will also develop and maintain essential data models, quality frameworks, and validation processes. Collaboration with data analysts, scientists, product teams, and business stakeholders is vital for delivering trusted data assets.

Ensure pipeline performance, reliability, and scalability while supporting cloud-based data platforms and data warehouses/lakehouses. Implement strong data governance, security, and compliance standards. Create comprehensive technical documentation and participate in code reviews to uphold engineering best practices. Troubleshoot production issues, conduct root-cause analysis, and contribute to automation and CI/CD initiatives.

We are seeking candidates with a Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related discipline. A minimum of 3 years of experience in data engineering, software engineering, or big data development is required.

Proficiency in developing ETL/ELT pipelines and working with large-scale datasets is essential. Experience with data warehouses, data lakes, and modern data architectures is expected. Solid command of SQL and Python for data processing and engineering tasks is a must.

Familiarity with cloud platforms like Azure, AWS, or Google Cloud is necessary. A strong understanding of data modeling, data quality, and data governance principles is required. Proven analytical and problem-solving skills, coupled with excellent communication and stakeholder collaboration abilities, are key. The ability to work independently with minimal supervision and manage multiple priorities is also crucial.