This company provides analytic data for the financial industry. Their goal is to provide transparency to avoid financial bubbles and downfalls, to make sure that investors and institutions are empowered to make sound investments.
They currently are looking for a Data Engineer who can leverage their strong experience with Python and database engineering while gaining exposure and growing into a more formal Data Science role. As a member on our Data Science Team you will be responsible for ETL and database work, efficiently parsing and storing data from thousands of financial institutions. You will manage the infrastructure and code base that processes data relating to millions of financial accounts each day. Additionally, you will have the opportunity to work with the Data Scientists on our team to develop machine learning pipelines to solve large scale classification, clustering, and natural language processing tasks using financial data.
Required Skills & Experience
• Experience with ETL and/or other Big Data processes.
• Experience writing production code in Python (ideally in the context of data processing or data science).
• Strong SQL experience, ideally with MSSQL or PostgreSQL and batch loading processes.
• 3-6 years of engineering experience in a professional environment, but skill fit is a higher priority to us than just work experience.
• Experience with Docker and with distributed systems such as Hadoop, Spark or Celery is a plus.
• B.S. or M.S. in Computer Science, or equivalent work experience.
• Excellent communication and collaboration skills. Able to work across multiple teams and discuss technical concepts to business development, operations, and other engineers.