Data Engineer

Must have: Airflow, Python, AWS, and SQL, 70 percent is support/monitoring, 30 percent development Sr. Data Engineer must have a broad and deep data skillset as well as strong analytical capabilities. In addition to being a hands-on individual contributor, the ideal candidate is a productive team player and a mentor to Junior Data Engineers. Additionally, we are looking for strong technical experts. • Actively participate in team technical discussions in all things data • Identify and address issues with data sets from multiple vendors • Identify and address code and data quality issues • Actively participate in code reviews and grooming sessions • Actively participate in technology architecture discussions for product development • Translate business requirements into strategy • Advocate for software best practices within your team as well as across engineering • Be ultra-responsive and capable of making instant decisions, always kicking the ball forward • Work on unique and interesting data challenges around architecting, building and managing pipelines that securely process hundreds of terabytes of data • Work closely with analysts and statisticians to ensure the validity of our processes Our engineers are expected to wear a number of hats and have the opportunity to touch all parts of the stack. Our stack includes Apache Spark, Scala, Redshift and an ever-growing list of many other cool technologies. Requirements • Airflow • Experience wrangling terabytes of big, complicated, imperfect data • Experience with AWS products (Redshift, EMR, S3, IAM, RDS, etc) • You have a deep understanding of scalable systems and you have large-scale engineering experience in an Agile development environment • Bachelor's degree in Computer Science or a related field (or 4 additional years of relevant work experience) • A strong understanding of data structures, algorithms, and effective software design • Significant development experience with a major modern language (e.g. Java, Scala, Python, Ruby, C/C++, etc.) • Significant experience working with structured and unstructured data at scale and comfort with a variety of different stores (key-value, document, columnar, etc.) as well as traditional RDBMS and data warehouses • Experience with or interest in AWS Glue, Redshift Spectrum and any other tools that enable data querying at scale • Experience writing unit, functional and integration tests • Comfort with version control systems (e.g. Git, SVN) • Excellent verbal and written communication skills; must work well in an agile, collaborative team environment