Data Engineer at Wizeline

What You Will Bring To The Team

We are looking for Senior Data Engineers to drive the architectural design, implementation plan, best practices, and testing plans for projects involving terabytes of data, which will serve as the foundation for advanced analytics and machine learning tasks to be performed by data scientists on top of that infrastructure.

Your day-to-day activities

• 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, managing structured and unstructured data while melding existing warehouse structures.
• Analyze, diagnose and identify bottlenecks in data workflows
• Participate in demos to clients as well as 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 General Programming Skills
• Solid experience with Python. If not proficient in Python, we expect the candidate to be proficient in other languages and prove their ability to learn new ones very quickly.
• Experience with Spark.
• Solid engineering foundations (good coding practices, good architectural design skills)
• Experience working with SQL in advanced scenarios that require heavy optimization
• 4+ years of experience with large-scale data engineering with emphasis on analytics and reporting
• 2+ years of experience developing on Hadoop-like Ecosystem
• Experience building cloud scalable, real time and high-performance Data Lake solutions.
• Proficiency designing and implementing ETL (Extract, Transform, load) processes, dealing with big volumes of data (terabytes of data which required distributed processing)
• Experience developing solution 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.