Data Engineer at T3W Business Solutions Inc

San Diego, California, United States -

Full Time

Start Date

Immediate

Expiry Date

03 Aug, 26

Salary

115000.0

Posted On

05 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, ETL/ELT, Data Modeling, Cloud Data Platforms, Databricks, Azure, AWS, Tableau, Power BI, Agile, Data Governance, API Development, Dimensional Modeling, PostgreSQL, MS SQL Server

Industry

Strategic Management Services

Description

Description The Data Engineer independently designs, builds, and maintains the data infrastructure that enables data-driven decision-making across the Naval Aviation Enterprise. Working within the NAAC/FRAG team, this individual operationalizes raw data from NAE source systems into reliable, analytics-ready pipelines and data products that support readiness reporting, predictive analytics, and enterprise metrics. This position performs all functional duties with minimal oversight and is expected to interface directly with analysts, software engineers, and government clients to understand data requirements and deliver scalable solutions. RESPONSIBILITIES Data Pipeline Development and Operations Design, build, and maintain automated Extract, Transform, and Load (ETL/ELT) pipelines to ingest data from NAE source systems including OOMA/DECKPLATE, AMSRR, NALCOMIS, MFOM, DRRS-N, RSUPPLY, and other aviation readiness data systems Monitor pipeline reliability, performance, and data quality; implement alerting and remediation procedures for pipeline failures Translate raw, unstructured, or semi-structured operational data into standardized, analytics-ready datasets Data Architecture and Modeling Design and implement relational and dimensional data models (star/snowflake schemas) to support analytical workloads and reporting requirements Develop and maintain data dictionaries, data flow diagrams, and schema documentation to support data governance and literacy goals Implement data partitioning, indexing, and query optimization strategies to ensure responsive performance across large datasets Cloud and Platform Engineering Develop and deploy data solutions on cloud platforms (e.g., Microsoft Azure, AWS) leveraging Platform-as-a-Service (PaaS) and Data-as-a-Service (DaaS) capabilities Integrate data pipelines with visualization and reporting tools including Tableau, Qlik, and Power BI to enable self-service analytics for NAE stakeholders Support configuration and administration of data stores including SQL databases, SharePoint data sources, and cloud data warehouses Analytics Enablement and Collaboration Partner with FRAG analysts to understand metrics requirements and translate analytical needs into structured data products and standardized data feeds Support the development of PESTO readiness metrics, financial metrics, aircraft material condition metrics, and predictive analytics per SOW §6.1.4 Assist in building and maintaining APIs and data access layers that enable downstream tools (PowerApps, PowerBI, PowerAutomate) to consume structured data Data Governance and Quality Enforce data governance standards and data quality controls in alignment with NAAC data governance policies and enterprise data literacy objectives Identify and resolve data discrepancies, duplication, and lineage issues across source systems Document all data assets, transformations, and business rules to support auditability and knowledge transfer Requirements Bachelor of Science/Arts in Computer Science, Information Systems, Data Science, Engineering, or related technical field and 3+ years of relevant professional experience in data engineering, data architecture, or a closely related discipline OR in lieu of degree 6 additional years of relevant experience may substitute for the Bachelor’s degree Minimum 3 years of hands-on experience designing and developing data pipelines, ETL processes, or data engineering workflows in a production environment Proficiency in Python for data engineering tasks (pandas, SQLAlchemy, requests, or equivalent libraries) Strong proficiency in SQL for data querying, transformation, stored procedures, and performance tuning across relational database platforms (e.g., PostgreSQL, MS SQL Server, MySQL) Experience with at least one cloud data platform (Databricks preferred) Familiarity with data warehousing concepts and dimensional modeling Demonstrated ability to integrate disparate data sources and produce clean, reliable datasets for downstream analytics Familiarity with Artificial Intelligence tools for programming and productivity Experience working in Agile development environments Must have an active Secret Clearance-Required Desired Qualifications Familiarity with NAE data systems: OOMA/DECKPLATE, AMSRR, NALCOMIS, MFOM, DRRS-N, or equivalent DoD logistics/readiness reporting systems Experience with Microsoft Power Platform (PowerBI, PowerApps, PowerAutomate, SharePoint) in a data integration or pipeline context Familiarity with Tableau or Qlik for data layer development supporting BI dashboards Knowledge of DoD data governance frameworks, data standards, or Navy data architecture policies Experience with CI/CD pipelines for data engineering workflows (e.g., Git, Azure DevOps) Familiarity with DoD Risk Management Framework (RMF) and Authority to Operate (ATO) processes as they apply to data systems This contractor and subcontractor shall abide by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability.

Responsibilities

Design, build, and maintain automated data pipelines and infrastructure to support data-driven decision-making for the Naval Aviation Enterprise. Collaborate with analysts and government clients to translate raw operational data into scalable, analytics-ready data products.