Data Engineering Analyst II

Description

Job Summary: Design, develop, and optimize scalable data pipelines, implementing ETL/ELT processes and data modeling for Data Lakehouse environments, ensuring data quality and performance. Key Highlights: 1. Work in a dynamic, collaborative, and welcoming environment 2. Encouraged to grow professionally 3. Collaborate with multidisciplinary teams and clients **It's fun to work in a company where people truly BELIEVE in what they're doing!** Job Description: Our BRLINK structure is seeking a Data Engineering Analyst II. If you enjoy working in a dynamic, collaborative, welcoming, and engaging environment where you are encouraged to grow professionally, then Ingram Micro is the perfect fit for you. **Key Responsibilities:** * Design, develop, and optimize scalable and resilient data pipelines, ensuring quality, governance, and performance. * Implement ETL/ELT processes and data modeling for Data Lakehouse, Data Warehouse, and Data Mesh environments. * Build and optimize solutions for large-scale data volumes, applying performance and cost optimization techniques. * Integrate data from multiple sources (on-premises and cloud), ensuring consistency and reliability. * Work with cloud services (AWS and/or Databricks) for data storage, processing, and orchestration. * Implement security, data privacy, and governance practices (encryption, access control, Lake Formation). * Automate workflows and tasks using orchestration tools (Apache Airflow, AWS Step Functions). * Collaborate with multidisciplinary teams and translate business requirements into technical solutions. * Participate in client meetings to understand requirements and propose technical solutions. * Document processes and solutions in an organized and accessible manner for the team. **Additional Information:** * Bachelor’s degree in Technology, Computer Science, Engineering, or related fields. * Proficiency in SQL and Python for data manipulation and transformation. * Practical experience in developing and maintaining production data pipelines.