About the position
As a Cloud Data Engineer at CNTXT, you will guide customers on how to ingest, store, process, analyze, and explore data on the Google Cloud Platform. You will work with clients and partners to implement data processing systems, data pipelines optimized for scaling, and troubleshoot potential deployment challenges.
What you'll do
- Guide customer implementations on the Google Cloud Platform.
- Perform builds and automations of customer implementations.
- Collaborate with clients to solve cloud challenges, especially challenges relating to data engineering.
- Setup and manage Google internal infrastructure and data pipelines for our clients.
- Work with the team to identify and qualify business opportunities, understand customer technical objectives, and develop the strategy to resolve technical blockers.
- Develop proofs of concept, presentations, and demos in order to take a prospect successfully through the evaluation process and make them satisfied customers.
- Partner with product management to prioritize solutions impacting customer adoption to Google Cloud.
- Travel to customer sites, conferences, and other related events as required.
- Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
- Minimum of 5 years of experience in technical sales, engineering, or equivalent experience in customer-facing roles.
- Experience in the data management domain, including data quality, data lineage, and data security
- Experience with data processing software and data processing algorithms.
- Experience in working with/on data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools, environments, and data structures.
- Direct experience in big data, information retrieval, data mining or machine learning as well as experiences in building multi-tier high availability applications with modern web technologies (such as NoSQL, MongoDB, SparkML, TensorFlow) is a plus.
- Experience with developing infrastructure as code and the DevOps discipline is a plus.