Senior Data Engineer
The ideal candidate is an experienced data engineer and can serve as a thought leader on the team for organizing structured and unstructured data, managing data pipelines, building data models, and scaling our data warehouses. Our data provides the best understanding of consumer purchase behavior, that needs daily updates and availability across many countries.
Our platform leverages a data store that performs heavy computation at runtime, as opposed to pre-materializing our datasets. In our industry, this has proven to be a huge business advantage, but becomes a challenge as our concurrent user count increases. Here's a comprehensive list of challenges that may present themselves as part of the role:
- What options exist to scale our data warehouse to support growing concurrency and report complexity?
- How would we process and organize a new stream of semi-structured data with 10m events/day?
- What solutions should be solved with a MPP data warehouse solutions versus a map-reduce system?
- Determine SLA strategy with Product & Business partners for new data sets
- When should we employ an ETL strategy versus and ELT strategy?
Along with a supporting cast of data engineers and application developers, this senior data warehouse lead will help provide answers and implement the solutions that allow Numerator to continue to build out the world's largest single-source set of purchase data across brands and retailers.
- BS or MS in Computer Science or equivalent work experience
- 4+ years of experience in the data warehouse space
- Expert in SQL, including advanced analytical query
- Experience working with a MPP data warehouse (Redshift)
- Experience in ETL design and tools (Talend, Pentaho Kettle, Informatica)
- Experience with schema design and data modeling
Exceptional candidates will have:
- Experience configuring and optimizing Vertica clusters
- Experience in working with map-reduce systems (Hadoop, Apache Spark)
- Experience in BI Development (Tableau, MicroStrategy)
- Experience with NoSQL Systems (Mongo, Cassandra, DynamoDB)
- Experience in data science and building models (R, Python/Pandas)
- Experience using terraform and/or ansible for infrastructure deployment
- Experience using variety of Amazon Web Services (EC2, ELB, RDS)
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.