Data Engineer ($60/hr)

We are seeking a highly skilled Data Engineer to join our team and play a critical role in designing, building, and maintaining robust data pipelines and systems. The ideal candidate will have hands-on expertise in Spark, Scala, and SQL, as well as a strong understanding of data modeling, data mining, and database design. This role requires a mix of technical depth, problem-solving ability, and analytical thinking to uncover insights from complex data sets and enable better decision-making across the organization. Key Responsibilities • Design, develop, and maintain scalable data pipelines and systems. • Use automated tools to extract data from primary and secondary sources. • Reverse engineer SQL queries and Scala code to understand functionality. • Clean and validate data by removing corrupted data, fixing coding errors, and resolving quality issues. • Perform in-depth analysis to assess the quality, meaning, and integrity of data. • Filter and refine data by reviewing reports and performance indicators to identify and correct problems. • Use statistical and analytical tools to identify, analyze, and interpret patterns and trends in complex data sets. • Develop and maintain database designs, data models, and techniques for data mining and segmentation. • Collaborate with programmers, engineers, and business stakeholders to identify process improvement opportunities and propose system modifications. • Prepare clear, insightful reports and dashboards for management, outlining trends, patterns, and predictions. • Contribute to data governance strategies and ensure data consistency across systems. • Support ongoing epics and projects by providing data mapping, query support, and technical expertise. Must-Have Skills • Strong knowledge of Spark, Scala, and SQL. • Ability to reverse engineer SQL queries and Scala code. • Experience in database design, data models, and data mining techniques. • Strong analytical skills to identify, interpret, and visualize patterns and trends in large datasets. Good-to-Have Skills • Hands-on experience with data processing platforms such as Hadoop, CouchDB, and Apache Spark. • Experience with statistical tools and programming languages like Python, R, SAS, SPSS, and Excel. • Familiarity with reporting tools and frameworks (Business Objects, ETL frameworks, JavaScript, XML). • Proficiency with data visualization platforms such as Tableau, Qlik, or similar tools. • Knowledge of how to create and apply algorithms to large datasets for problem-solving. • Exposure to data governance practices and large-scale data mapping (e.g., ACRS, MARSHA).