Our CompanyAt Kynetec, we're proud to be at the forefront of the intersection between agriculture, sustainability, and animal health. We’re redefining our industry with unparalleled insights and leading technology, whilst on an ambitious growth plan to supersede our influence from the food on our plates, to the health of our livestock and the care of our beloved pets at home.We owe our success to our industry experts. They are the driving force behind our reputation as a global leader in the industry - Their innovative ideas and expertise have helped us achieve new heights. From seasoned insights specialists, and client leaders to innovative tech genius. What connects us? A shared passion for Agriculture and Animal Health! We don’t settle for “business as usual”.Each day, we are taking strides towards transforming our industry and improving the lives of people and animals around the world. If you’re looking for a company who challenges the norm and fosters a culture of innovation, Kynetec is the place for you.The RoleThe Senior Data Engineer will play a pivotal role in building, optimizing, and maintaining our data pipeline architecture, ensuring data quality and accessibility for cross-functional teams. This role will be a key member of our Advanced Analytics team and will focus on building and supporting our data pipelines in a Databricks environment.Responsibilities - Create and maintain large-scale data processing systems and infrastructure. - Build robust, performant, and scalable data pipelines to ingest, transform, and store complex data from multiple sources. - Collaborate with data science and software engineering team members to provide required data in an accessible, timely, and accurate manner. - Optimize and refine processes, algorithms, and systems to enhance data quality and reliability. - Ensure data privacy and security compliance. - Implement monitoring, logging, and alert systems to ensure data pipeline health and performance. - Collaborate with infrastructure and IT teams to ensure optimal data storage and retrieval mechanisms. - Drive the optimization, testing, and tooling to improve data quality. - Mentor junior data engineers, imparting knowledge and promoting best practices. - Stay updated with emerging technologies and introduce them as needed to improve the data engineering ecosystem.Requirements - Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree is a plus. - 5+ years of experience in data engineering, ETL processes, and database systems. - Proficient in SQL, Python, PySpark, and experience with big data platforms. - Experience creating data pipelines and working with workflow management tools. - Strong experience with relational and NoSQL databases. - Working experience in cloud platforms like AWS and Azure. - Excellent communication and collaboration skills.Preferred Skills - Experience with Databricks platform, Azure Data Factory, Kedro framework - Experience with Machine Learning processes - Relevant Industry Certifications