• Demonstrated experience with designing cloud-native architectures using cloud services such as AWS, Google, IBM, and Oracle.
•  Demonstrated experience designing and operating big data systems.
•  Demonstrated experience building and optimizing performance of large scale graph databases (tens of billions of edges) using DynamoDB or new enhanced capabilities.
• Demonstrated experience developing and operating graph traversal capabilities using data graphing tool traversal capabilities built upon Apache Gremlin or new enhanced capabilities.
• Demonstrated experience developing and operating NoSQL solutions to complex big data applications.
•  Demonstrated experience in data modeling for performance, partition sharding, record/event aggregation workflows, stream processing, and metrics gathering.
•  Demonstrated experience designing and operating large-scale serverless geospatial indexes built with GeoMESA.
•  Demonstrated experience with partition and sort key design and implementation to ensure consistent performance.
•  Demonstrated experience with aggregation operations to de-duplicate records on continuous data feeds.
•  Demonstrated subject matter expertise experience with relational databases to noSQL.
•  Demonstrated experience building and operating high performance data processing pipelines using Lambda, Step Functions and PySpark.
•  Demonstrated experience building high quality User Interface/User experiences with the React framework and webGL.
•  Demonstrated experience designing and operating large scale graph databases using Apache Cassandra.
•  Demonstrated experience performing in-depth technical analysis of large-scale graph databases to develop implementation strategies for search optimizations.
•  Demonstrated experience developing technical capabilities for processing, persistence and search of datasets that are collected or maintained using standards common in the Sponsor's community.
•  Demonstrated experience facilitating engineering discussions across teams representing multiple stakeholders to develop and execute implementation strategies that meet mission needs.
•  Demonstrated experience developing Machine Learning Operations (MLOps) pipelines for large scale application.
• Demonstrated experience maintaining configuration of software using configuration management resources such as GitHub.
• Demonstrated experience designing, building and operating big data systems, such as persistence, partitioning, indexing, at scale of trillions of records/events.
•  Demonstrated experience with Niagara Files (NiFi) applications or new enhanced capabilities.
•  Demonstrated experience developing and operating Kubernetes infrastructure.
•  Demonstrated experience supporting engineering efforts that will contribute to delivery of capabilities such as datasets and functionality such as communications, geospatial workflows.
• Demonstrated experience implementing DevSecOps and agile development in production environments.
• Demonstrated experience with agile software development and testing.
•  Demonstrated experience with federal security, regulatory and compliance requirements and security accreditation package development.
• Demonstrated experience with data security and governance using centralized security controls like LDAP, encrypting the data, and auditing access to the data.
•  Demonstrated experience with specialized technologies that are optimized for the particular use of the data, such as relational databases, a NoSQL database (Cassandra), or object storage.
•  Demonstrated experience with Apache, TINKERPOP, GREMLIN and/or JANUSGRAPH to design, develop, implement and maintain system
•  Demonstrated knowledge of Graph Database to design, develop, implement and maintain system.
•  Demonstrated experience with C or C to write interfaces.
• Demonstrated experience using centralized security controls like LDAP, encrypting data, and auditing access to data.
•  Demonstrated experience with:

• Databases: Postgres, MariaDB, ELK, Minio, AWS S3, Neo4j, MongoDB, noSQL
• Languages: Python (pypi libraries)
• Operating Systems: Centos7, RockyLinux8
• Orchestration: Kubernetes, Docker, Docker-Compose, Docker-Swarm
• Development Tools: vscode, gitlab, jupyterhub/notebooks, MATLAB
• Environments: large collaboration and development environments
• Data types: Unstructured, structured, or semi-structured data, including: CSV, JSON, JSONL, AVRO, Protocol Buffers, Parquet, etc.

Desired Skills and demonstrated Experience

• (Demonstrated experience with designing cloud-native architectures using Sponsors cloud services.
•  Demonstrated experience designing and operating big data systems within the Sponsors policy and regulatory environment.
• Demonstrated experience developing and operating graph traversal capabilities using the Sponsors data graphing tool traversal capabilities built upon Apache Gremlin.
•  Demonstrated experience building and operating high performance data processing pipelines using Lambda, Step Functions and PySpark on the Sponsors infrastructure with EMR.
•  Demonstrated experience working with the Sponsor's enterprise services used for Data Management, including the enterprise catalog service (and associated APIs), and Policy Decision Points (PDPs).
• Demonstrated experience developing Machine Learning Operations (MLOps) pipelines for large scale application in the Sponsor's environment.
•  Demonstrated experience and understanding of IT Service Management and common SLA measurements.
•  Demonstrated experience presenting solutions, requirements, and presentations to diverse audiences.
•  Demonstrated experience working with container orchestration technologies such as AWS ECS, AWS Fargate, and Kubernetes or other enhanced capabilities available
•  Demonstrated experience in managing large operational cloud environments spanning multiple tenants using Multi-Account management, AWS Well Architected Best Practices, and AWS Organization Units/Service Control Policies (OU/SCP).
•  Demonstrated experience with Micro-services such as building decoupled systems, utilizing RESTful endpoints and lightweight systems.
•  Demonstrated experience in total systems perspectives, including a technical understanding of systems and applications relationships, dependencies, and requirements of hardware and software components.
• Demonstrated experience consulting with customers to determine present and future user needs.
• Demonstrated experience providing frequent contact with customers, traceability within program documents, and the overall computing environment and architecture.
• Certifications:
  • AWS Certified Solutions Architect
  • AWS Machine Learning Certification(s)
  • Agile certification
  • Azure
  • Security
  • GSEC
  • CCNA