Create and deliver recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders.
Design, develop, and maintain reliable data pipelines to collect, process, and store data from various data sources.
Implement data quality checks and monitoring to ensure data accuracy and integrity.
Collaborate with cross-functional teams (data science, engineering, product managers, sales and finance) to understand data requirements and deliver data solutions.
Enhance data infrastructure for performance, efficiency to meet evolving business needs.
Minimum qualifications:
Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
3 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
Experience with database administration techniques or data engineering, and writing software in Java, C++, Python, Go, or JavaScript.
Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.
Preferred qualifications:
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 applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow).
Experience architecting, developing software, or production-grade Big Data solutions in virtualized environments.
