Data Engineer

Position Overview

SteerBridge seeks a highly skilled and motivated Data Engineer II to join our team supporting the F-35 AI/ML Spares Project. As the most advanced fighter jet in the world the F-35 strengthens national security enhances global partnerships and powers economic growth. Our F-35 AI/ML Spares Project applies advanced computational analytics to revolutionize supply chain management in the aerospace industry harnessing the power of AI/ML to increase parts availability reduce maintenance wait times and maximize aircraft collaboration with the National Center for Manufacturing Sciences (NCMS) we are on a mission to deliver exceptional solutions that will redefine operational readiness for the F-35 program and beyond.

In this mid-level role you will build and maintain AWS-based ETL/ELT pipelines curated analytical datasets and reporting workflows that support operational decision-making. You will design scalable data infrastructure that powers business intelligence machine learning and operational analytics performing data engineering tasks on-site within the existing systems of record with multiple databases. This position also involves mentoring and collaborating with Marines at the squadron level requiring a deep understanding of squadron-specific operations and a commitment to improving data entry and indexing practices. You will be a crucial link between our existing systems and data development collaborating closely with data scientists analysts and operational partners.

Key Responsibilities

Lead end-to-end data pipeline operations design develop and maintain robust ETL/ELT pipelines on AWS (AWS Glue Amazon Redshift Amazon S3) using modern orchestration tools such as Apache Airflow dbt or Prefect.

Use Azure Databricks (Spark) and Azure Data Factory to manage and schedule data pipelines and workflows.

Build and optimize data models in cloud data warehouses (Snowflake BigQuery or Redshift); maintain data in S3 buckets and Blob storage.

Integrate data from diverse sources including REST/SOAP APIs event streams (Kafka) relational and non-relational databases and SaaS platforms.

Create index query and update SQL tables/servers; run and update Python and/or JavaScript code to parse data.

Monitor pipeline health enforce data quality controls (schema validation null checks duplicate detection) troubleshoot data issues and implement alerting and observability best practices.

Develop and implement data acquisition quality assurance and management protocols; document all data collection cleaning and analyses for internal and external users.

Use schedulers and APIs to obtain near real-time data; automate workflows and processes using Python or other scripting languages.

Partner with data scientists and analysts to deliver clean well-documented datasets and data products; collaborate with and support the data science team to produce deliverables.

Contribute to data governance standards including lineage cataloging and access controls.

Mentor and collaborate with Marines at the squadron level to improve data entry and indexing practices.

Assist with maintenance and development of internal analytics data architecture.

Design write and disseminate innovative and visually appealing reports for diverse audiences.

Participate in code reviews architecture discussions and cross-functional planning sessions.

Evaluate and recommend new tools and technologies to improve the data platform.

Required Qualifications

Education & Experience

35 years of professional experience in data engineering or a closely related role.

Bachelors Degree in Computer Science or related field; three (3) years of additional relevant experience may substitute for education (minimum six years total experience without degree).

U.S. Citizenship required.

Active security clearance or the ability to obtain one is required.

Technical Skills

Strong proficiency in Python (PySpark pandas) and SQL for data processing and pipeline development; SQL fluency including CTEs window functions and complex joins.

Hands-on experience with at least one cloud data warehouse (Snowflake BigQuery or Redshift).

Experience configuring or monitoring data pipelines in cloud platforms (AWS preferred; Oracle Azure Google also considered).

Familiarity with analytics deployment architectures including Python containerized Docker and Kubernetes.

Experience with Spark/Databricks for streaming data analytics with preferred experience in graph data machine learning and AI applications.

Experience using Azure Data Factory to schedule pipelines and manage data flows.

Ability to connect and work with APIs (REST SOAP HTTP methods).

Experience with workflow orchestration tools such as Apache Airflow dbt or Prefect.

Solid understanding of data modeling concepts: star schema data vault medallion architecture data lineage and source-to-target mapping.

Familiarity with data visualization tools including Tableau Power BI Elasticsearch/Kibana R or Alteryx.

Experience with version control (Git) CI/CD practices and production deployment workflows.

Experience integrating data; familiarity with cleaning merging standardizing documenting and securing data.

Interpersonal & Professional Skills

Strong communication skills with the ability to translate technical concepts for non-technical and operational stakeholders.

Ability to develop relationships with collaborators program providers community partners and military personnel.

Able to successfully prioritize and manage multiple critical projects simultaneously with a high degree of accuracy.

Experience working on applied data projects involving diverse organizations to collect analyze and interpret data.

Preferred Qualifications

AWS Professional or Specialty Certification or the ability to obtain one (highly preferred).

Experience supporting DoD and/or VA missions.

At least two (2) years using SQL professionally with proficiency in R or Python.

Cloud project experience using AWS Google Oracle and/or Azure.

Experience with ML/NLP/AI including Neural Networks and Supervised/Unsupervised algorithms for anomaly detection forecasting and modeling.

Experience with streaming data technologies such as Apache Kafka or AWS Kinesis.

Proficiency in HTTP Methods Postman development/testing of REST and/or SOAP APIs and CRUD actions.

Familiarity with data catalog and lineage tools such as DataHub Alation or Monte Carlo.

Knowledge of infrastructure-as-code tools such as Terraform or Pulumi.

Exposure to ML pipelines and feature stores.

Demonstrated high proficiency in statistical analysis software: Power BI Tableau Elasticsearch/Kibana Alteryx Python or R.

Deep understanding of data quality issues with applied experience in quality assurance.

Proficiency in each phase of the software development lifecycle.

Masters degree in Computer Science Engineering Mathematics or a related field (or equivalent experience).

Excellent writing presentation and research design skills; track record of communicating complex concepts to diverse audiences.

Benefits