Data Engineering Team Lead
2 days left
- Full Time
Working at MIT offers opportunities, an environment, a culture – and benefits – that just aren’t found together anywhere else. If you’re curious, motivated, want to be part of a unique community, and help shape the future – then take a look at this opportunity.
DATA ENGINEERING TEAM LEAD, edX, to lead the data engineering team to architect and build out data pipelines and analytics infrastructure. Will collaborate on prototyping and deploying data-driven solutions to business problems and help edX find the right mix of talent, technology, and process that allows it to most effectively leverage data to fulfill its mission of providing high quality education to everyone, everywhere. Responsibilities include establishing strong working relationships with stakeholders as the vision for data engineering is built; providing hands-on leadership to a team of two to four software engineers to design and start building next-generation data pipelines and analytics infrastructure; writing code; leading the team in finding and implementing material process improvements; collaborating across organizational boundaries, including providing guidance and support to engineers, data scientists, and other business stakeholders; demonstrating a “you build it, you run it” mindset of ownership; and holding regular 1:1s with direct reports, providing coaching and mentoring.
REQUIRED: seven years’ hands-on experience leading data engineering projects such as data architecture and data warehouse implementations; strong focus on practical business outcomes; experience leading a team of engineers; experience building data pipelines and ETLs using distributed processing and streaming data tools, e.g., Hadoop, Spark, Storm, or Kafka; experience designing and implementing multi-terabyte data warehouses in MPP database systems, e.g., Vertica, RedShift, or BigQuery; skill with Python or similar language; and excellent communication skills. Experience with deploying machine learning algorithms in production, clickstream data or learning analytics (xAPI, Caliper), business intelligence tools such as Tableau or Power BI to enable consumption of data across an organization, and cloud deployments (AWS) preferred.