Principal / Sr Principal Data Analytics Engineer

Northrop Grumman•Melbourne, FL

10d•$98,400 - $184,200•Hybrid

About The Position

At Northrop Grumman, we offer employees incredible opportunities to work on revolutionary systems that impact people's lives globally and for generations to come. Our pioneering and inventive spirit has led us to be at the forefront of technological advancements. We seek individuals with bold new ideas, courage, and a pioneering spirit to join us in inventing the future. Our culture fosters intellectual curiosity, cognitive diversity, and encourages employees to bring their whole selves to work, driven by an insatiable desire to achieve the seemingly impossible. Our employees are not just part of history; they are making history. Are you motivated to work in an environment that challenges you, drives continuous innovation, and focuses on solutions that make a difference for customers? Northrop Grumman Aerospace Systems relies on our team to provide critical insights that drive performance across a broad range of strategic activities. We are looking for a passionate Data Analytics Engineer to design and develop automated, end-to-end, Extract, Transform, and Load (ETL) pipelines and Data Analytics/Visualization solutions from disparate data sources. You will share ownership of the technical vision and direction for advanced analytics systems that transform how we perceive and utilize data. We are seeking self-motivated, hardworking individuals who have demonstrated the ability to find innovative solutions to complex technical problems. This role is hybrid and requires regular onsite presence in Melbourne, FL. Candidates must be within a commutable distance of the Melbourne site.

Requirements

Bachelor’s degree in a STEM related discipline with 5 years of experience in data engineering, analytics engineering, or a related field OR Master's degree with 3 years of data engineering, analytics engineering, or a related field (Principal Level).
Bachelor’s degree in a STEM related discipline with 8 years of experience in data engineering, analytics engineering, or a related field OR Master's degree with 6 years of data engineering, analytics engineering, or a related field (Senior Principal Level).
Strong proficiency in SQL and Python.
Strong proficiency developing and deploying Tableau dashboards and the ability to translate business needs into visual insights.
Experience with version control and Agile Software Development.
Strong problem‑solving skills, attention to detail, and ability to work in fast‑paced, cross‑functional teams.
Excellent communication skills, both written and verbal, to convey technical concepts to non‑technical stakeholders.
Active US Government Secret clearance required to apply with ability to obtain Special Access Program (SAP) clearances.

Nice To Haves

Master’s degree in Computer Science, Engineering, Statistics, or a quantitative discipline with experience in data engineering, analytics engineering, or a related field.
Hands‑on experience with modern orchestration tools (e.g., Airflow, dbt, Dagster, Prefect, etc.) and data ecosystem platforms (e.g., Databricks, Denodo, Snowflake, etc.).
Deep understanding of data modeling concepts, dimensional modeling, and data warehousing methodologies.
Proven track record of building and maintaining production‑grade data pipelines.

Responsibilities

Design, develop, and maintain scalable data pipelines and ETL processes across multiple data sources.
Build and optimize data models (star, snowflake, data vault) for analytics and reporting.
Implement robust data quality, validation, and monitoring frameworks to ensure reliability of downstream insights.
Collaborate with data scientists, product managers, and business stakeholders to translate analytical requirements into technical specifications.
Create reusable, documented analytics code libraries and SDKs to accelerate self‑service analytics.
Implement practices in version control, testing, and CI/CD for data workflows.
Evaluate emerging data technologies and recommend improvements to the analytics stack.
Ensure compliance with data governance, security, and privacy policies (e.g., GDPR, CCPA).
Develop and maintain Tableau dashboards, KPI scorecards, and ad‑hoc querying tools for executive and operational audiences.