Join our dynamic team as a Lead Associate Data Engineer and play a pivotal role in shaping our Engineering as a Service/Operate division. This position focuses on creating and maintaining robust data pipelines and platforms essential for analytics, reporting, and advanced AI/ML solutions. You'll tackle moderately complex data engineering challenges independently while collaborating closely with business and technology stakeholders to deliver impactful data solutions that meet enterprise-wide needs.

As a key technical resource, you will guide team members, share best practices, and drive the continuous enhancement of our data platforms and engineering methodologies, ensuring we maintain a cutting-edge data ecosystem.

Key responsibilities include designing, developing, and maintaining scalable data ingestion, transformation, and integration pipelines. You will build and optimize ETL/ELT workflows to efficiently process diverse data types from multiple sources.

Translate business and customer requirements into effective technical data solutions. Identify and resolve complex data challenges and engineering problems. Develop and maintain data models, robust data quality frameworks, and validation processes.

Collaborate with data analysts, scientists, product teams, and business stakeholders to deliver trusted data assets. Monitor and optimize pipeline performance, reliability, scalability, and cost-effectiveness. Support cloud-based data platforms and data warehouse/lakehouse environments.

Implement comprehensive data governance, security, lineage, and compliance standards. Create detailed technical documentation, design specifications, and operational procedures. Participate in code reviews, promote engineering best practices for development, testing, and deployment.

Troubleshoot production issues, conduct root-cause analysis, and implement sustainable solutions. Contribute to automation, CI/CD processes, and ongoing improvement initiatives across the data ecosystem.

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.

Demonstrated experience in developing ETL/ELT pipelines and working with large-scale datasets is essential. Familiarity with data warehouses, data lakes, and modern data architectures is expected. Strong proficiency in SQL and Python for data processing and engineering is a must.

Knowledge of cloud-based data platforms such as Azure, AWS, or Google Cloud is required. A solid understanding of data modeling, data quality, and data governance principles is important. You should possess proven analytical and problem-solving skills, coupled with excellent communication and stakeholder collaboration abilities.

Proven ability to work independently with minimal supervision and manage multiple priorities effectively is crucial for success in this role.