Data Engineer (Dataviz / Power Bi)

Overview Our client is a U.S.-based company that provides technical expertise, testing, and certification services to the global food and agricultural industry. The role is to build, maintain, and modernize data pipelines that process large-scale regulatory data and transform it into usable datasets for downstream applications and APIs. The engineer will work hands-on with Python, SQL, and related tools to untangle legacy pipelines, migrate processes to maintainable platforms such as Airflow, and ensure data quality for client-facing products. The role requires strong technical ability and a consulting mindset to learn undocumented systems, troubleshoot gaps, and design scalable solutions. Responsibilities Design, build, and maintain data pipelines and ETL/ELT processes using Python and SQL (Snowflake, DBT, Airflow). Migrate legacy pipelines to maintainable platforms and improve data reliability, accuracy, and scalability. Monitor data jobs and pipelines, respond to alerts, and minimize downtime. Maintain and enhance DBT models and SQL scripts to support evolving business needs and data accuracy. Oversee data warehouse operations, including access control, query performance, and resource utilization. Perform root cause analysis of data job failures and implement preventive measures. Collaborate with data engineers, analysts, and stakeholders to support operational data needs and troubleshooting. Identify opportunities to automate manual tasks and improve pipeline efficiency. Document operational procedures, job schedules, and incident logs; provide regular updates on system health and performance. Qualifications Minimum 7 years’ experience using Python for data analysis, extraction, transformation, and handling large datasets. Proficiency in Python 3 with libraries/tools for data engineering (Pandas, NumPy, Jupyter Notebooks). Strong SQL skills with Oracle, Postgres, or MS SQL Server; solid database design, data modeling, and data warehousing concepts. Experience with Snowflake, DBT, Airflow; knowledge of data governance and data quality practices. Familiarity with Agile software development and collaborative, cross-functional teams. College degree or equivalent in computer science, software development, engineering, information systems, math, or related field. Preferred: NoSQL (MongoDB, DynamoDB, Cosmos DB), cloud platforms (AWS, Azure, GCP), Infrastructure as Code (Terraform). What We Offer Professional development opportunities and ongoing skills evolution. Remote-friendly environment with potential opportunities outside the country. Collaborative and innovative culture with emphasis on teamwork. J-18808-Ljbffr

Location: Rio Grande do Norte, Brazil, BR

Posted Date: 9/11/2025