Join our team as a Data Engineer and play a key role in building and maintaining robust data pipelines and platforms. This position is perfect for an experienced professional looking to contribute to analytics, reporting, and AI/ML initiatives.

You will independently tackle moderately complex data engineering challenges. Close collaboration with business and technology stakeholders is essential to understand needs and deliver effective data solutions supporting enterprise-wide data requirements.

As a technical mentor, you will guide team members on best practices and actively participate in enhancing our data platforms and engineering processes. This is an opportunity to make a significant impact in a dynamic environment.

Design, develop, and maintain scalable data pipelines for ingestion, transformation, and integration. Optimize ETL/ELT workflows to process diverse data sources. Translate business and customer requirements into technical data solutions. Address and resolve complex data challenges and engineering problems. Develop and uphold data models, quality frameworks, and validation processes. Collaborate with cross-functional teams to deliver reliable data assets. Monitor and optimize pipeline performance, scalability, and cost efficiency. Support cloud-based data platforms and data warehouse/lakehouse environments. Implement robust data governance, security, lineage, and compliance standards. Create comprehensive technical documentation and operational procedures. Participate in code reviews, promoting best practices in development, testing, and deployment. Troubleshoot production issues, conduct root-cause analysis, and implement lasting solutions. Contribute to automation, CI/CD, and continuous improvement initiatives. Adhere to all employment contract terms, company policies, and directives.

A Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field is required.

We are seeking candidates with 3+ years of experience in data engineering, software engineering, or big data development.

Essential skills include experience developing ETL/ELT pipelines, working with large datasets, and strong proficiency in SQL and Python for data processing.

Familiarity with cloud data platforms like Azure, AWS, or Google Cloud, along with a solid understanding of data modeling, data quality, and data governance principles, is crucial.

Excellent analytical, problem-solving, communication, and stakeholder collaboration skills are a must. The ability to work independently with minimal supervision and manage multiple priorities is expected.