Data Engineer

T3W Business Solutions Inc
San Diego, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 260K

Job location

San Diego, United States of America

Tech stack

API
Agile Methodologies
Artificial Intelligence
Amazon Web Services (AWS)
Business Analytics Applications
Data analysis
Azure
Big Data
Cloud Foundry
Information Systems
Computer Programming
Data as a Services
Data Architecture
Information Engineering
Data Governance
Data Infrastructure
Data Integration
ETL
Data Security
Data Stores
Data Systems
Data Warehousing
Relational Databases
Database Queries
Digital Assets
Dimensional Modeling
Python
PostgreSQL
Microsoft SQL Server
MySQL
Operational Data Store
Performance Tuning
Query Optimization
Raw Data
Power BI
SharePoint
SQL Stored Procedures
SQL Databases
SQLAlchemy
Tableau
Enterprise Data Management
Cloud Platform System
Microsoft Power Automate
Indexer
GIT
SC Clearance
Data Layers
Pandas
Information Technology
QlikView
Tools for Reporting
Data Pipelines
Powerapps
Databricks

Job 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., 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, * 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, * 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

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