Lead Data Engineer
Our client is looking for a Lead Data Engineer to drive the Data sciences and Insights platform implementation across the group for products including video, mobile, OTT, and web. He or she will be responsible for establishing and maintaining software best practices, coding standards, engineering best practices, SOA architecture, and assisting with tool and technology evaluations that will dictate execution for the team. The successful candidate will be passionate about media and technology and have great hands-on technical, leadership, and communication skills. Drive the entire technology culture and help steer test-driven development, agile processes, and a design-first engineering culture that is constantly experimenting and learning.
The ideal candidate will be a self-starter driven by their own curiosity and sense of urgency. They will be able to maintain focus through helping prioritize and streamline requirements. Candidates should have 5 to 10 years of experience doing whatever it takes to get the job done.
We are looking to partner with an expert and thought leader who can help our team given their:
· History of delivering applied solutions in challenging and ambiguous environments
· Familiar with large system analytics and gathering, manipulating, and presenting data to effect decision-making
· Experience with Google Clout Platform especially their data suite including Big Query, Datastore, BigTable
· ETL processes utilizing technologies such Airflow, DataProc, SPARK, SPARQL, SQL
· Familiarity with data concepts such as Normalization, Relational, Star, Cube, Document Databases
· Experience using information visualization tools for Reporting and/or Drill-Down analysis (Eg. Matplot, OpenGL, DataStudio, Tableau, Power BI, etc.)
· Knowledgeable about algorithmic concepts from at least one information-centric discipline (eg. statistics, Machine Learning, information processing, natural language processing, information retrieval, etc.)
· Knowledgeable about the relative computational complexity and scalability of particular approaches
· Experience managing hardware deployments using tools such as virtualization and containerization (eg. Docker, Kubernetes)
· Capable of managing cloud-based operations in a continuous integration and deployment (CI/CD) setting (eg. cloud infrastructure, deployment, operations, and monitoring)