Data Engineer
Summary
Data Engineer consults on big-data solutions, designs cloud and on-prem databases, and delivers tutorials and code samples for clients using tools like Hadoop, Spark, and Google BigQuery.
Responsibilities
- Act as a trusted technical advisor to customers and solve complex Big Data challenges.
- Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders.
- Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment for big data
- Travel up to 30% of the time for meetings, technical reviews, and onsite delivery activities.
- Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities.
Qualifications
- Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
- Experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
- Experience in Google Cloud (BQ / other data related tools).
- Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.
- Experience programming in Python and SQL.
- Experience in technical consulting.
- Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
- Experience working with Big Data, information retrieval, data mining, or machine learning.
- Experience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow).
- Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.