Data Engineer

You can’t improve what you can’t measure, so we’ve built the best-in-class analytics product for content marketers. We’re looking for a strong data engineer to help us build and expand our big data analytics ETL and API. This is a top initiative within the company and with our best in class talent network and content production platform we have a lot of interesting data to analyze. Come help us guide the industry with new insights.
You should love working at a startup because it means driving initiatives with little supervision, solving tough, yet exciting problems each day, working with a passionate and smart team in an agile environment, and making our customers happy and successful.

What You’ll Do:
– Collaborate with product management, data scientists, and engineers to define and translate feature requirements into sound, creative software designs
– Creatively solve problems by bringing a unique perspective
– Produce solid, thoroughly tested features (including automated tests)
– Plan and execute software releases using agile methods
– Big data modeling
– Build and expand our ETL
– Work with our data scientists to explore, define, create, and deploy analytics algorithms

Who You Are:
– 3-5+ years software engineering experience, ideally with Python or Ruby
– Strong software engineering & architecture fundamentals
– BS in Computer Science or equivalent experience
– BDD & TDD proficient with test frameworks such as Python’s NoseTests or Ruby’s RSpec
– Experience building RESTful APIs, ideally with Python or Ruby
– Experience with Big Data technology – Apache Spark/Hadoop, Redshift, Elasticsearch, and more
– Experience with SQL (Postgres, MySQL, Oracle, etc)
– You want to be part of a growing and entrepreneurial company with proven users and business model
– You want to learn more, build your experience, and contribute within a fast-paced agile environment

Bonus:
– You understand machine learning, NLP, and other advanced analytical techniques
– Experience working with AWS and/or Google cloud technology