SAIC - McLean, VA

posted about 2 months ago

Full-time - Mid Level
McLean, VA
Professional, Scientific, and Technical Services

About the position

The position involves supporting a program that utilizes integrated discrete technologies to manage massive data processing, storage, modeling, and analytics across thousands of unique data sources. The primary goal is to facilitate threat identification and analysis while aiding in the achievement of both tactical and strategic objectives. The data platform capability, which serves as the backbone for various applications, accelerates operations by leveraging technologies and systems for data processing and modeling. This role requires the development and application of data processing technologies such as Python, SPARK, Java, SQL, Jenkins, PyPi, Terraform, Cloudera, ElasticSearch, Pentaho, Apache NiFi, and Apache Hop. The successful candidate will be responsible for performing data processing and developing methodologies to meet analytic requirements in clustered computing environments. Additionally, the role includes supporting downstream systems and capabilities of external customer organizations that rely on the data platform. This involves creating integration plans that utilize new data processing, modeling, and storage technologies, including cloud environments. The candidate will evaluate data collections to assess their potential value to the customer’s data platform and generate assessments to support data acquisition and engineering activities. This will ensure that data is effectively integrated into the data platform systems to maximize its value. The position also entails performing and supporting data modeling and engineering activities, refining existing models, and creating new models and data feeds to support both existing and new analytic methodologies, all under customer oversight.

Responsibilities

  • Support a program leveraging integrated discrete technologies for data processing, storage, modeling, and analytics.
  • Develop and use data processing technologies to perform data processing and support analytic requirements in clustered computing environments.
  • Support downstream systems and capabilities of external customer organizations dependent on the data platform via APIs.
  • Develop integration plans that capitalize on new data processing, modeling, and storage technologies, including cloud environments.
  • Evaluate data collections to assess their potential value-add to the customer's data platform.
  • Generate assessments about data and support activities for data acquisition and engineering.
  • Perform and support data modeling and engineering activities for integrating new data into the data platform's corpus.
  • Refine existing models and create new models and data feeds to support analytic methodologies.

Requirements

  • Proficiency in Python, SPARK, Java, SQL, Jenkins, PyPi, Terraform, Cloudera, ElasticSearch, Pentaho, Apache NiFi, and Apache Hop.
  • Experience in performing data processing and developing methodologies for analytic requirements in clustered computing environments.
  • Ability to perform and support data modeling and engineering activities for data integration.
  • Undergraduate degree in mathematics, computer science, engineering, or a similar scientific or technical discipline.
  • Graduate degree in computer science, information systems, engineering, or another scientific or technical discipline is preferred.

Nice-to-haves

  • Experience using Enterprise Control Language (ECL) and the Lexis-Nexis High Performance Cluster Computing (HPCC) platform.
  • Experience performing All-Source data analysis for analytic support.
  • Experience developing custom algorithms for massive data stores.
  • Experience in technical analysis support using massive data processing systems.
  • Experience writing cables and planning program activities such as hardware and software installation.
  • Experience deploying web applications in a cloud-managed environment, including DevOps and security configuration management.
  • Experience developing and maintaining cloud infrastructure services such as EC2, ELB, RDS, S3, and VPC.
  • Experience in planning and executing activities to support documentation for data compliance requirements.
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