Job Details

ID #45845670
State Virginia
City Richmond
Job type Permanent
Salary USD TBD TBD
Source Federal Reserve Bank
Showed 2022-09-20
Date 2022-09-19
Deadline 2022-11-17
Category Et cetera
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Cloud Data Analytics Engineer

Virginia, Richmond, 23173 Richmond USA

Vacancy expired!

Company Federal Reserve Bank of Richmond

The Enterprise Data Services team has an immediate opening for a Cloud Data Engineer. Our team delivers a centralized data and analytics platform that provides advanced data migration and analytics solutions for our bank district customers. We work with state-of-the-art technologies that are part of the next generation data ecosystem, which includes tools used for data storage, data processing, data integration, data lakes, data warehousing, and data analytics.

This position will work directly with the Enterprise Data Analytics (EDA) team. The EDA team is responsible for evaluating and implementing solutions to on-board, build and deploy analytic solutions in the Cloud. You will work cross-functionally with Data Architects, Product Owners, Design Engineers, Developers and Business Analysts in a rapidly evolving environment, identifying solutions, building, and implementing Infrastructure as Code using our CI/CD pipeline.

As part of the National IT team, our Enterprise Data Services team is partnered with multiple business lines, our Board of Governors and other IT groups within the Federal Reserve System. You will have an opportunity to showcase your critical thinking and technical skills across many disciplines. This role will be instrumental in shaping the development and support of our product roadmaps and will advance our cloud data analytics platforms.

What You Will Do:
  • Understand technology vision and strategic direction of business needs
  • Develop product roadmaps in alignment with other data products and business roadmaps
  • Design integrated solution in alignment with design patterns, blueprints, guidelines, and standard methodologies for products
  • Participate in defining technical requirements that outlines solution for enabling data analytics within an AWS cloud environment.
  • Participate in developing architecture and design conceptual solutions by incorporating cloud native and 3rd party vendor products
  • Provide analysis of current state, future state, and define key outcomes for an IT data platform strategy.
  • Participate in research and perform POCs (proofs of concept) with emerging technologies and adopt industry best practices in the data space for advancing the cloud data platform.
  • Demonstrate automation through Infrastructure as a code to increase build efficiency in the cloud
  • Develop scripting to integrate multiple data sources to data and analytics platform
  • Build platform supporting rehydration and HA
  • Build end to end automation to support and maintain software currency
  • Create automation services for builds using Terraform, Python, and OS shell scripts.
  • Develop validation and certification process through automation tools
  • Develop multi-layered build, installation, configuration, patching, regression testing, and rollback scripts in each environment.
  • Develop data streaming, migration, and replication solutions
  • Create patching process to compare different versions of the configuration settings.
  • Provide consulting and guidance on business solution development in the data and analytics space and cloud technologies
  • Demonstrate leadership, collaboration, exceptional communication, negotiation, strategic and influencing skills to gain consensus and produce the best solutions.
  • Engage with Senior leadership, business leaders at the Federal Reserve and the Board to share the business value.
  • Promote collaboration across business and IT organizations

Qualifications:
  • Must have Business Acumen skills to understand and anticipate business priorities
  • Demonstrates mutual respect, embraces diversity, and acts with authenticity
  • Demonstrates analytical and problem-solving skills.
  • Subject matter expertise in transforming data platform and analytics space.
  • Bachelor's degree in Computer Science, Management Information Systems, Computer Engineering, or related field or equivalent work experience; advance degree preferred
  • Experience in designing and building large-scale solutions in an enterprise setting in both On-Prem/ AWS
  • 5+ years in designing and building with all aspects of cloud design, development, and implementation, experience with analytics, including Jupyter Notebook and/or SageMaker
  • 3+ years in designing, building, and deploying solutions using Docker containers
  • Experience in developing product roadmap in alignment with other data products and business roadmaps
  • Experience with leveraging CI/CD pipelines and GitLab is a must
  • Hands on experience in Terraform, Python, and OS shell scripts including automation tools
  • Hands on experience in one or more languages such as Java, JavaScript
  • Advanced proficiency in cloud specific solutions related to ECS/EKS and ECR
  • Experience with other AWS data related services including various compute and storage offerings
  • Experience with RDS, NOSQL Databases, RDBMS and in-memory databases.
  • Strong background in data structures, networking, performance, and scalability
  • Microservices experience is strongly preferred
  • Must be familiar with Agile methodologies and able to work in an Agile manner
  • Must have a very strong application development background

Full Time / Part Time Full time

Regular / Temporary Regular

Job Exempt (Yes / No) Yes

Job Category Information Technology

Work Shift First (United States of America)

The Federal Reserve Banks believe that diversity and inclusion among our employees is critical to our success as an organization, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.

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