Design, develop and implement data infrastructure and pipelines that collect, connect, centralize and curate data from various internal and external data sources. You will ensure that architectures support the needs of the business, and recommend ways to improve data reliability, efficiency and quality.
- Participate in data architecture discussions to understand target data structures, required data transformations and inform architectural approach based on best practices for data processing.
- Lead detailed exploration of new internal and external source data to advise strategic initiatives led by the Product, Artificial Intelligence and Business Intelligence teams.
- Influence technical and business strategy by making insightful contributions to team priorities and overall data processing approach.
- Work in close collaboration with data-minded colleagues focused on back-end (microservice) development, business intelligence reporting, machine learning and artificial intelligence models.
- Participate in the hiring and mentoring of other data engineers.
- Bachelor’s degree in Computer Science, Information Management, Data Science, Analytics or related field or equivalent experience.
- 6 or more years of experience as a data engineer on enterprise-level data solutions.
- Experience in SQL and scripting for automation with Python, Perl or Ruby.
- Experience working with relational and unstructured databases and enterprise data warehouses, including MySQL, PostgreSQL, MongoDB, SQL Server or Oracle.
- Master’s degree in Information Management, Data Science, Analytics or related field.
- Expert in SQL and Python for scripting automation.
- Experience building open source data pipeline systems such as AirFlow, Hadoop or Kafka.
- Experience with Spark, Presto, Hive or other map/reduce “big data” systems and services.
Job ID: 4231