Enterprise Data Architect

INTERVIEW

• 10+ year managing enterprise level database and data warehouse environments along with data modelling and data analysis.
• 8+ year experience developing reference architecture, principles and standards.
• 8+ year experience with relational database technologies and administration (
  SQL, Oracle, Hadoop, RedShift, Teradata, etc.).
• 8+ year experience with relational
  NoSQL databases including DynamoDB, MongoDB, or similar.
• 5+ year experience with
  Redshift database administration and data modelling (performance tuning, indexing and database/query optimization for high-speed big data consumption).
• 5+ year experience working with
  AWS services for large datasets (
  EMR, S3, CLI, CloudWatch, RDS, DynamoDB, etc.).
• 7+ year experience with
  ETL, data integration, and other business intelligence tools like
  Informatica, PowerBI, Tableau, etc.
• 5+ year experience with SQL database administration and data modelling.
• 5+ year experience with
  Python scripting and ID federation.
• Experience with big data batch processing tools:
  Hadoop MapReduce, Elasticsearch, PIG, Hive, Cascading/Scalding, Apache Spark, AWS EMR or similar
• Experience with stream-processing systems:
  Kinesis, Kafka, MQTT or similar
• Ability to write JSON, XML, YAML and other data definition schemas
• Good knowledge of data management, data integration, and database development techniques.
• Ability to relate architectural decisions and recommendations to business needs.
• Ability to regularly learn and adopt new technologies.
• Strong analytical and problem-solving skills. Exercises independent judgment in methods, techniques and evaluation criteria for obtaining results.
• Ability to communicate written and verbal across all levels of the organization and work with diverse project teams.
• Ability to provide a leadership role for the work group through knowledge in area of specialization.