Job Description
At arenaflex, we're on a mission to revolutionize the retail industry through innovative technology and data-driven insights. As a key member of our Supported Hunt Information group, you'll play a crucial role in designing, implementing, and maintaining data pipelines, datasets, and ETL processes for arenaflex's Supported Pursuit Publishing platform. If you're passionate about working with big data, cloud computing, and cutting-edge technologies, we want to hear from you! About arenaflex arenaflex is a leading retailer that's pushing the boundaries of innovation and technology.
Our Worldwide Tech team is a community of programmers, data scientists, network security experts, and operations professionals who are shaping the future of retail. We're a human-driven organization that's passionate about developing our team members and acquiring experts like you to help us grow. Whether you're just starting your career or looking for a new challenge, we offer opportunities for growth, learning, and development. Key Responsibilities As a Full Stack Data Entry Specialist, you'll be responsible for: * Accurately inputting, updating, and maintaining data into our database systems * Designing and implementing robust, adaptable data pipelines for ingesting, transforming, and storing large volumes of data to support marketing on arenaflex.com and its subsidiaries * Working on cloud platforms like Azure and bolthires Cloud for data storage, processing, and analysis * Developing and deploying large-scale, containerized applications using Docker and Kubernetes on public clouds like bolthires GCP and bolthires Azure * Collaborating with other scrum teams, QA, Product, Program Management, and Partner Operations, while working with cross-functional project development teams * Participating in 24/7 on-call rotations to investigate production issues across cross-functional teams What You'll Bring * Demonstrated aptitude in data design concepts, data set planning, ETL cycles, and data mining * Proficiency in working with data technologies including SQL, Python, Flash, Scala, Hadoop, and related tools and frameworks * Experience with ETL tools like Apache NiFi * Solid skills working with social databases (e.g., Azure SQL) and NoSQL datasets (e.g., Cassandra) * Experience with real-time message processing using Apache Kafka * Experience in designing and implementing data models for efficient storage and recovery * A growth-oriented mindset and a willingness to raise the technical bar, as well as identify potential opportunities for improving existing processes, tools, and frameworks to achieve high scale and efficiency * Experience working with Docker and Kubernetes, as well as Distributed Computing Services like bolthires GCP and bolthires Azure, and Distributed Storage Frameworks like Hive and HBase Essential Qualifications * Bachelor's degree in Computer Science, Information Technology, or related field * 2+ years of experience in data engineering, data science, or related field * Strong understanding of data design concepts, data set planning, ETL cycles, and data mining * Proficiency in working with data technologies including SQL, Python, Flash, Scala, Hadoop, and related tools and frameworks * Experience with ETL tools like Apache NiFi * Solid skills working with social databases (e.g., Azure SQL) and NoSQL datasets (e.g., Cassandra) Preferred Qualifications * Master's degree in Computer Science, Information Technology, or related field * 5+ years of experience in data engineering, data science, or related field * Experience with real-time message processing using Apache Kafka * Experience in designing and implementing data models for efficient storage and recovery * Experience working with Docker and Kubernetes, as well as Distributed Computing Services like bolthires GCP and bolthires Azure, and Distributed Storage Frameworks like Hive and HBase Skills and Competencies * Strong analytical and problem-solving skills * Excellent communication and collaboration skills, with the ability to present to both technical and non-technical audiences * A growth-oriented mindset and a willingness to learn and adapt to new technologies and processes * Strong attention to detail and ability to work in a fast-paced environment * Ability to work independently and as part of a team
Career Growth Opportunities and Learning Benefits At arenaflex, we're committed to developing our team members and providing opportunities for growth and learning.
As a Full Stack Data Entry Specialist, you'll have access to: * Ongoing training and development programs to enhance your skills and knowledge * Opportunities to work on high-impact projects and contribute to the development of new technologies and processes * Collaborative and dynamic work environment with a team of experts in data engineering, data science, and related fields * Flexible work arrangements, including remote work options and flexible hours * Competitive compensation and benefits package, including health insurance, retirement savings plan, and paid time off Work Environment and Company Culture arenaflex is a human-driven organization that values collaboration, innovation, and growth.
Our team members are passionate about developing new technologies and processes that can make a real impact on people's lives. We're committed to creating a work environment that's inclusive, diverse, and supportive of all team members. Compensation, Perks, and Benefits arenaflex offers a competitive compensation and benefits package, including: * Competitive salary and bonus structure * Comprehensive health insurance plan * Retirement savings plan with company match * Paid time off and holidays * Flexible work arrangements, including remote work options and flexible hours * Access to ongoing training and development programs * Opportunities to work on high-impact projects and contribute to the development of new technologies and processes If you're passionate about working with big data, cloud computing, and cutting-edge technologies, we want to hear from you!
to of experts in data engineering, data science, and related fields.