Junior/Middle Data Engineer (Spark, SQL, Linux)

Company InformationFounded in 2018, Data Nest is a dynamic and innovative company specialising in credit scoring, lead generation services and other products. By harnessing the power of Data Analytics and AI, we help finance companies to reduce their credit loss, to widen their consumer base, and to fasten their release of new financial services.We aim to transform the financial landscape through the strategic application of data analytics and AI and make a better society where financial services are accessible for everyone.Are you ready to be part of a dynamic and passionate team at the forefront of revolutionising the financial industry? Look no further – Data Nest is the place to be!Why Choose Data Nest?Market-Leading Benefits:At Data Nest, we believe that our success is fueled by the talent and dedication of our team members. That's why we're proud to offer top-notch benefits that set us apart from the rest!Innovation at its Core: We're not just another company; we're a hub of innovation, where your ideas are valued, and your creativity is encouraged.Exciting Challenges: We tackle challenges head-on and view them as opportunities for growth. Join us in solving complex problems and pushing the boundaries of what's possible in the world of data analytics and AI.Apply now - Your future start here !A. JOB DESCRIPTIONWe are looking for innovative data engineers to build and evolve our leading financial products. You will work with a team of young and talented engineers to build robust and scalable big data pipelines, conduct advanced research in implementing state-of-the-art ML and AI techniques, build high-quality data services that are both streaming and batch-based.B. RESPONSIBILITIESDevelop and maintain data pipelines to ensure data quality for machine learning model development.Operationalize data processes - provide the team with ad-hoc analysis, automated dashboards, and self-service reporting tools so that everyone gets a good sense of the state of the businessCollaborate with Data Analysts to build BI reporting systems and analytical dashboards.Support Data Scientists in retrieving, processing, and preparing data for model training.Efficiently prioritize and execute what’s important: prioritize for both speed and impact, and aggressively optimize for return by focusing on work output that scales well and is reusableMaintain a culture of high quality output and exceptional customer service: effectively communicate at all levels, ensure that work gets done well and on time, respond effectively to unexpected obstacles and reallocate resources as necessary