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Lead moderately complex initiatives within Technology and contribute to large scale data processing framework initiatives related to enterprise strategy deliverables
Build and maintain optimized and highly available data pipelines that facilitate deeper analysis and reporting
Review and analyze moderately complex business, operational or technical challenges that require an in-depth evaluation of variable factors
Oversee the data integration work, including developing a data model, maintaining a data warehouse and analytics environment, and writing scripts for data integration and analysis
Resolve moderately complex issues and lead teams to meet data engineering deliverables while leveraging solid understanding of data information policies, procedures and compliance requirements
Collaborate and consult with colleagues and managers to resolve data engineering issues and achieve strategic goals
Requirements:
4+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
3+ years of Spark experience
3+ experience on Abinitio
3+ years of Python or other scripting language
3+ years of data warehouse experience
3+ years of SQL experience
Ability to conduct code reviews with a focus on testability and code coverage.
Should have experience working in an Agile environment using Scrum or Kanban.
Fluent in communication
Should have executed end to end projects in data engineering
1+ years of strong experience with Hadoop
1+ years of strong experience with Hive
1+ years of strong experience with Python
1+ years of experience with Kubernetes
1+ years of experience with Docker
1+ years of experience with Google Big Query
2+ years of experience with Autosys
2 years presenting to technical and executive audiences
Good knowledge of non-relational DBMS platforms, (MongoDB or Neo4j)
Good knowledge of real-time data streaming via Kafka
Good knowledge of Cloud ecosystems such as Google Cloud Platform