Company OverviewFounded in 1993, Baxter Planning has 30+ years of industry expertise setting the standard for SaaS in the service supply chain planning space. With a strong and growing customer base, we are developing new products and solutions as well as finding new ways to extend and enhance our established products building on our success in the market. We combine the agility and innovation of a start-up with the stability of an established, profitable, global company.
As a Data Engineer for Baxter Planning, will be responsible for designing, implementing, and optimizing data systems to support our data lake/data mesh infrastructure and data processing needs. We are looking for an individual who possesses strong technical skills, problem-solving abilities, and a passion for data engineering, with a specific emphasis on AWS, AWS Glue, and data lake expertise.Interested? Join us!ResponsibilitiesDesign, implement, and optimize data systems to support our data mesh infrastructure.Utilize AWS Glue for data extraction, transformation, and loading (ETL) processes.Refactor and improve existing data systems for enhanced efficiency and performance.Collaborate closely with product development and production support teams to meet their data engineering requirements.Participate actively in peer code reviews to maintain code quality and consistency.Diagnose and resolve production issues, offering corrective measures and workarounds when necessary.Continuously assess key performance indicators (KPIs) and identify opportunities for improvements and optimizations within our data mesh.Keep up-to-date with emerging technologies, especially in AI and software development, and apply them innovatively in projects.Qualifications3+ years of relevant experience in data engineering.Knowledge in ETL concepts within modern data applications.Good SQL skills, with a focus on PostgreSQL and query optimization.Proficiency in Python programming.Knowledge of AWS services and AWS Glue, Athena and Lambda FunctionsFamiliarity with agile development practices.Demonstrated ability in analysis and design of data systems.Preferred QualificationsExperience in building data systems with real-time data streams (e.g., Kafka, Kinesis).Strong understanding of complex data architecture, especially for data lake environments.Bachelor of Science degree in a technical major (Computer Science, Engineering, Mathematics) or equivalent industry experience.Familiarity with other ETL tools (Pentaho, Informatica, SSIS, etc.).Knowledge or experience with microservices and messaging systems.Experience with supply chain management is a plus.Familiarity with MongoDB is a plus.
#J-18808-Ljbffr
