Wizeline is a global digital services company helping mid-size to Fortune 500 companies build, scale, and deliver high-quality digital products and services. We thrive in solving our customer's challenges through human-centered experiences, digital core modernization, and intelligence everywhere (AI/ML and data). We help them succeed in building digital capabilities that bring technology to the core of their business. Your Day-to-Day This job posting is for Data Engineer on our team. Here's what you'll be doing in your day-to-day work: Design and implement product features in collaboration with product owners, report developers, product analysts, architects, and business partners within an Agile / Scrum methodology. Design and implement data platforms for large-scale, high-performance, and scalable requirements, integrating data from several data sources, and managing structured and unstructured data while melding existing warehouse structures. Analyze, diagnose and identify bottlenecks in data workflows. Participate in demos to clients and requirements elicitation and translation to systems requirements (functional and nonfunctional). Constantly monitor, refine and report on the performance of data management systems. To be successful in this role, you must have: Strong Programming Skills with Python. Solid experience with Spark. Experience working with SQL in advanced scenarios that require heavy optimization. 7+ years of experience with large-scale data engineering with an emphasis on analytics and reporting. 3+ years of experience developing on Hadoop-like Ecosystem. Experience building cloud-scalable, real-time and high-performance Data Lake solutions. Proficiency in designing and implementing ETL (Extract, Transform, load) processes, dealing with big volumes of data (terabytes of data which required distributed processing). Experience developing solutions within Cloud Services (AWS, GCP, or Azure). Experience with NoSQL databases such as Apache HBase, MongoDB, or Cassandra. Experience in data streams processing technologies including Kafka, Spark Streaming, etc. Advanced English level. #J-18808-Ljbffr