Design and implement data products and features in collaboration with product owners, data analysts, and business partners using Agile / Scrum methodology; contribute to overall architecture, frameworks and patterns for processing and storing large data volumes; evaluate and utilize new technologies/tools/frameworks centered around high-volume data processing; drive the implementation of new data projects and the optimization of existing solutions; translate product backlog items into engineering designs and logical units of work; profile and analyze data for the purpose of designing scalable solutions; define and apply appropriate data acquisition and consumption strategies for given technical scenarios; design and implement distributed data processing pipelines using tools and languages prevalent in the big data ecosystem; build utilities, user defined functions, libraries, and frameworks to better enable data flow patterns; implement complex automated routines using workflow orchestration tools; drive collaborative reviews of designs, code, and test plans; work with architecture, engineering leads and other teams to ensure quality solutions are implemented, and engineering standard methodologies are defined and followed; anticipate, identify and tackle issues concerning data management to improve data quality; build and incorporate automated unit tests and participate in integration testing efforts; utilize and advance continuous integration and deployment frameworks; solve complex data issues and perform root cause analysis; collaborate closely with Product team counterparts; work across teams to resolve operational & performance issues; provide work estimates and represent work progress and challenges; identify and remove technical bottlenecks for your engineering squad; and provide leadership, guidance and mentorship to other data engineers. Telecommuting is available from anywhere in the U.S., except from SD, VT, and WV.

• Python;

• SQL;

• Spark;

• AWS;

• Big Data;

• Airflow;

• Data Warehousing;

• Data Modeling;

• SCALA;

• Docker;

• Data Transformation and Integration; and

• Data analysis