Make data engineering more reliable, scalable, and usable. As a Senior Analytics Engineer with General Dynamics Information Technology, you will design automated pipelines and analytics-ready datasets, then deliver dashboards and analytical models that help teams make faster, more informed decisions across multiple business and program areas.
This fully remote role supports end-to-end work from data preparation through modeling and reporting, with opportunities to collaborate with data engineers, analysts, software developers, and stakeholders. The likely salary range for this position is $127,500 to $172,500, depending on experience and qualifications.
Responsibilities
- Design, build, and maintain automated, scalable ETL/ELT pipelines using Python, SQL, and cloud-based tools to integrate, transform, and validate structured and unstructured data.
- Develop and manage analytics-ready data models and workflows (for example in Databricks or similar platforms) to support reporting, self-service analytics, and advanced data science use cases.
- Implement CI/CD practices with GitLab to keep analytics and data engineering processes reliable, versioned, and repeatable.
- Build interactive dashboards and reports using Tableau, Power BI, or similar tools to deliver complex analysis to business and technical stakeholders.
- Perform data mining, cleaning, and manipulation with SQL and Python (including Pandas and NumPy) to support statistical analysis, visualizations, and decision-support tools.
- Own end-to-end analytical and modeling activities such as exploratory data analysis, feature preparation, model validation, and documentation, with experience in AI or predictive modeling considered a plus.
- Collaborate across teams to translate business requirements into effective data models, pipelines, and visualizations.
- Compile and maintain metadata, data dictionaries, and technical documentation, and produce recurring and ad-hoc reports for leadership.
- Handle urgent and ad-hoc data requests and support collaborative research and analysis across program areas.
- Provide technical guidance and mentorship on analytics best practices, Python scripting, data modeling, and workflow automation.
Requirements
- Bachelor’s degree in a quantitative field (data science, Computer Science, Statistics, Mathematics, Engineering, or related) plus 5+ years of experience, or 3+ years with a Master’s degree in analytics engineering, data engineering, or data analysis.
- Strong proficiency in Python, SQL, and Git/GitLab, including experience building ETL/ELT pipelines with CI/CD and data engineering best practices.
- Experience with relational and non-relational databases (for example Oracle and PostgreSQL) and creating executive-ready dashboards using Tableau or Power BI.
- Strong analytical and problem-solving skills with attention to detail, including the ability to work with large, complex datasets and communicate insights to technical and non-technical audiences.
- Ability to work independently and collaboratively in fast-paced, agile environments, with excellent written and verbal communication skills.
- Fully remote role with a Public Trust (or ability to obtain it); US citizenship required.
Technologies
Python, SQL, GitLab, Git, Tableau, Power BI, Databricks, Pandas, NumPy, Airflow, MLflow, Oracle, PostgreSQL, AWS, CI/CD, ETL, ELT
Work Requirements
- Travel Required: None
- Citizenship: U.S. Citizenship Required
- Years of Experience: 5+ years of related experience (may vary based on technical training, certification(s), or degree)
Identity Verification Process
- Identity verification process leveraging advanced biometrics and artificial intelligence
- Expected to be on camera during virtual interviews
- May be required to be on camera and authorize collection, processing, and use of biometric data for identity verification and security purposes
