Data and Infrastructure Consultant (4886) at SMX

, , United States -

Full Time

Start Date

Immediate

Expiry Date

11 Mar, 26

Salary

0.0

Posted On

11 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Pyspark, Databricks, Data Pipelines, Dev/Ops, CI/CD, Gitlab, Data Integration, Database Design, Cloud Architecture, Analytical Skills, Problem-Solving, Decision-Making, Knowledge Sharing, Software Engineering, ERP Systems

Industry

IT Services and IT Consulting

Description

cBEYONData is seeking a highly skilled and experienced team member to join our team in support of configuration and build of data pipeline and integrated data sets to support Data Science activities for a Federal customer. The focus across the broader program includes ingesting and integrating data from the ERP and Non-ERP systems while ensuring that the Infrastructure is properly sized and maintained to support the user base. If you are interested in joining a high performing team with advancement opportunities, then look no further! Essential Duties & Responsibilities: Design new solutions using Databricks (Python, Pyspark) to deliver capabilities meeting business functional requirements. Design modifications to existing data model solutions as needed. Promote code into production using Gitlab. Define test cases and verify test results to ensure solutions are functioning as designed. Build data models and reports using datasets from ERPs and legacy systems. Develop and load data from existing Army ERP’s by building data pipelines. Required Skills & Experience: Active DoD Secret security clearance are required 10 years of related work experience Strong analytical, problem-solving, and decision-making skills. Bachelor's degree in Computer Science or related field Minimum of 5 years of hands on development experience and proficiency in Python and Pyspark. Experience with Databricks, developing data pipelines and workflow automation Experience with Dev/Ops and CI/CD pipelines using Gitlab. Experience ingesting data from Army ERP and Non-ERP systems. Experience integrating data from GFEBS, LMP, GCSS-A and AESIP ERP’s. Familiarity with database design and architecture; relational and non-relational Ability to work cross-functionally, and participate in discussions Knowledge of cloud architecture: commercial cloud vendors (AWS/Azure) Competence with software engineering tools and processes (estimation, issue tracking, version control, debugging, etc.) Proven ability to work independently on assigned tasks without any supervision. Proven experience in knowledge sharing (i.e., code reviews, solid documentation) Driven, self-directed personality Strong sense of mission and commitment to making a difference Application Deadline: December 31, 2025 #LI-SA1 At SMX®, we are a team of technical and domain experts dedicated to enabling your mission. From priority national security initiatives for the DoD to highly assured and compliant solutions for healthcare, we understand that digital transformation is key to your future success. We share your vision for the future and strive to accelerate your impact on the world. We bring both cutting edge technology and an expansive view of what’s possible to every engagement. Our delivery model and unique approaches harness our deep technical and domain knowledge, providing forward-looking insights and practical solutions to power secure mission acceleration. SMX is an Equal Opportunity employer including disabilities and veterans. Selected applicant may be subject to a background investigation and/or education verification. SMX does not sponsor a new applicant for employment authorization or immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

Responsibilities

The consultant will design new solutions and modify existing data models to support Data Science activities for a Federal customer. Responsibilities include building data pipelines, integrating data from various systems, and ensuring the infrastructure is maintained.