Join our team as a Lead Associate in Data Engineering. This role focuses on creating robust and scalable data pipelines and platforms essential for advanced analytics, reporting, and AI/ML initiatives. You will tackle moderately complex data engineering challenges independently, collaborating closely with business and technology stakeholders to deliver impactful data solutions.

As a technical resource, you'll provide guidance on best practices to team members and drive continuous improvements in our data platforms and engineering processes. This is an exciting opportunity to shape enterprise data capabilities and foster innovation.

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 sources, and translate business requirements into technical data solutions.

Further duties involve identifying and resolving complex engineering problems, developing data models, quality frameworks, and validation processes. Collaboration with cross-functional teams to deliver trusted data assets, monitoring pipeline performance, and ensuring data governance, security, and compliance are also critical aspects of this role.

We are seeking candidates with a Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field, coupled with at least 3 years of experience in data engineering or software development. A strong command of SQL and Python for data manipulation and engineering is essential.

Proficiency in working with large-scale datasets, data warehouses, and data lakes is required. Familiarity with cloud data platforms like Azure, AWS, or Google Cloud, along with a solid understanding of data modeling and governance principles, is expected. Excellent analytical, problem-solving, and communication skills are a must.