Data Engineer

1 month ago

Arlington, United States Elder Research Full time
Data Engineer (cleared)

Location: Arlington, VA (Hybrid in The Washington DC area)

Clearance: US Public Trust

People Centered. Data Driven

Elder Research Inc. is a Data Science consulting firm specialized in providing analytic solutions to clients in Commercial and Government industries. Providing analytic solutions to hundreds of companies across numerous industries, our team enjoys a great variety in the type of work they do and exposure to a wide range of techniques and tools. We are trusted advisors to our clients, building lasting relationships and partnering as preferred analytics providers. We use a variety of programming languages and tools to create analytic solutions, often fitting within our clients' environment and needs.

Summary of Position:

As a Data Engineer, you will work directly with clients, managers, and technical staff to understand business needs, develop technical plans, and deliver data-driven analytical solutions and tools that solve client problems. The Data Engineer will primarily create and deploy robust, repeatable, and automated data pipelines that will ingest and transform raw data to support various advanced analytics and machine learning models. The resulting pipeline should be developed to be deployed into existing large-scale applications or different data visualization platforms available.

This position will be part of our Government Civilian Team serving Federal Civilian agencies as our primary customers. To be considered for this position, you must be currently eligible to legally obtain a US Public Trust issued by the US. Government.

Essential Functions:
  • Strong troubleshooting and problem-solving capabilities
  • Demonstrated experience with various types and sizes of data sets, both quantitative and text
  • Work collaboratively with data scientists, data analysts, and client engagement managers to create and deploy dynamic data applications or data visualization tools that help our customers make meaningful business decisions.
  • Writing re-usable code in Python, SQL, Java or other languages, and working to refine it through code review and discussion
  • Develop and deploy robust data pipelines and end-to-end systems in an air-gapped environment
  • Participate in every stage of the engineering lifecycle, from ideation and requirements gathering through implementation, testing, deployment, and maintenance
  • Provide leadership and coordination for certain stages of the engineering lifecycle as needed
  • Perform other technical tasks as needed, including writing project reports, managing, implementing, and/or maintaining technical infrastructure, etc.
  • Ability to consider both long-term stability and scalability while taking a user-focused approach to development and deployment.
  • Meetings and discussions with clients and co-workers to refine understanding of the business problem at hand.
  • Preparing presentations, writing reports (technical and non-technical), and working to communicate technical results to clients with varying levels of analytic sophistication.
  • Ability to work independently in a collaborative, dynamic, cross-functional environment.
  • Demonstrate strong communication and consulting skills, facilitating effective collaboration within a diverse team.
Job Specifications/Requirements:
  • Undergraduate and graduate degrees in engineering, computer science, analytics, math, finance, accounting, management information systems, social sciences, physics, or decision science.
  • Design, build, and deploy data engineering pipelines that extracts, transforms raw data into analytics base tables to support downstream machine learning models using languages such as Python, R and SQL
  • Develop end-to-end ML pipelines, responsible for integration from back to front end in on-premises and cloud environments.
  • Collaborate closely with data scientists, data analysts, client engagement managers, and product managers to understand business requirements and provide solutions.
  • Improve and modernize existing ML pipelines and operations, emphasizing best practices and efficiency gains.
  • Work in a fast-paced environment, contributing to a collaborative and agile development process.
  • Experience engaging and interacting with clients, stakeholders and subject matter experts (SMEs) to understand, gather and document requirements.
  • Comfortable learning new things and working outside of your comfort zone.
  • Communicate clearly both verbally and in writing to teammates and clients.
  • Humble and willing to learn, teach, and share ideas.
  • Travel to and work on-site at clients both local and non-local. Number of days at client site vary depending on project requirements.
  • Must currently possess a Public Trust Clearance
Desired Skills
  • Advanced degree (MS) in a relevant field (analytics, math, statistics, computer science, management information systems, social sciences, engineering, physics, decision science, or business, etc.,)
  • Experience using version control (e.g. git, svn, Mercurial) and collaborative programming techniques (e.g. pair programming, code reviews)
  • Experience with containerization and environment management (venv, conda, etc.,)
  • Experience with one or more technologies, such as R Shiny, Databricks, AWS, Azure
  • Familiarity with vector, object, and document storage databases
  • Experience implementing data engineering processes in a remote, austere environment to include using bash,
  • Experience with business intelligence and data visualization platforms (Power BI, Tableau, etc.,).
  • Understanding of the data analytics lifecycle (e.g. CRISP-DM).

Elder Research, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

To be considered for this position, you must be eligible to legally obtain a US Public Trust.

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