ResponsibilitiesPeraton is looking to hire an Data Science Engineer in the Washington DC Metro area. This role will be a remote position. At times, the role will also require travel to the Quantico client site when necessary.
What you'll do:
- Data Science Engineer designs, builds, and scales an organization's foundational data infrastructure. Beyond simply constructing data pipelines.
- Experience designing and building Data Lakes, Data Warehouses, and scalable data platforms in the cloud
- The successful candidate should have of experience in data engineering, including building data pipelines and warehouses
- Supports technical activities across the contract, and drives continuous improvement and innovation into program operations.
- Advises on technology alternatives related to processing, data storage, data access, application development, and enterprise architecture decisions as needed.
- Establish coding best practices and align complex data architectures with overarching business goals.
- Use APIs to push and pull data from various data systems and platforms
- Excellent listening, interpersonal, communication and problem solving skills.
- General data manipulation skills: read in data, process and clean it, transform and recode it, merge different data sets together, reformat data between wide and long, etc.
- Build and optimize ETL/ELT pipelines using glue and python to move and transform data across fabric.
- Package, curate, and version datasets for LM fine-tuning and model training jobs on Bedrock and Sagemaker.
- Enforce CUI handling requirements, automate PII detection and maintain Audit trails, e.g. Amazon Macie.
Qualifications
What you'll need:
- Education: 8 years experience with a BS/BA, 6 years with a MS/MA, 3 years with a PhD or 12 years of experience in lieu of a degre
- Clearance: active Secret clearance
- Demonstrates strong expertise in AWS architecture, security in the SDLC, and communication of technical risk and architecture decisions to executive audiences.
- Experience designing and building Data Lakes, Data Warehouses, and scalable data platforms in the cloud
- Experience with programming skills like Java, SQL, Scala, Python, R, defining schema and software engineering best practices including secure, testable, and maintainable code and database (eg SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis)
- Demonstrate a deep understanding of data engineering principles and techniques.
- Ability to work effectively in teams, in both a lead and support role.
- Ability to learn new techniques and troubleshoot code without support, ex. find answers to common programming challenges on Google etc.
- Ability to work effectively in teams, in both a lead and support role as needed
- Must be local to the Washington DC Metro area
Target Salary Range$135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
