Analytics Engineer

General Dynamics Information Technology, Inc.; United States; Remote; USD 128,000 - 173,000; Full time

Job summary

General Dynamics Information Technology, Inc. seeks a Principal Analytics Engineer to design scalable data pipelines and analytics datasets. You will develop dashboards and models that drive data-informed decisions and operational efficiency across multiple programs.

The role sits at the intersection of data engineering, analytics, and business intelligence, collaborating with data engineers, analysts, and stakeholders to deliver insights and guidance for critical missions.

Qualifications

• Bachelor’s degree in a quantitative field with 5+ years in analytics engineering, data engineering, or data analysis (or 3+ years with a Master).
• Strong proficiency in Python, SQL, Git/GitLab, and ETL/ELT pipelines with CI/CD and best practices.
• Experience with relational and non-relational databases (e.g., Oracle, PostgreSQL) and executive-ready dashboards using Tableau or Power BI.

Responsibilities

• Design, build, and maintain automated, scalable ETL/ELT data pipelines using Python, SQL, and cloud-based tools.
• Develop analytics-ready data models and workflows to support reporting, self-service analytics, and AI/ML use cases.
• Implement CI/CD practices using GitLab for data workflows and ensure versioned, repeatable processes.
• Create interactive dashboards and reports using Tableau/Power BI to deliver insights to stakeholders.
• Perform data mining and manipulation with SQL and Python to support analyses and decision tools.
• Conduct end-to-end modeling work including EDA, feature preparation, and model validation; AI/ML experience is a plus.
• Collaborate with cross-functional teams to translate requirements into data models and visualizations.
• Maintain metadata, data dictionaries, and technical documentation; produce recurring/ad-hoc leadership reports.
• Respond to ad-hoc data requests and support cross-program research.

Skills

Data Modeling

Programming Languages

Structured Query Language

Tools

GitLab CI/CD

Tableau

Job description

Job Qualifications

Data Modeling, GitLab CI/CD, Programming Languages, Structured Query Language (SQL), Tableau (Software)

Job Description

Type of Requisition: Regular

Clearance Level Must Currently Possess: None

Clearance Level Must Be Able To Obtain: Top Secret

Public Trust/Other Required: BI Full 6C (T4)

Job Family: Data Science and Data Engineering

Skills: Data Modeling, GitLab CI/CD, Programming Languages, Structured Query Language (SQL), Tableau (Software)

Certifications: None

Experience: 5 + years of related experience

US Citizenship Required: Yes

The Principal Analytics Engineer provides advanced analytics and data engineering support across multiple business and program areas. This role sits at the intersection of data engineering, analytics, and business intelligence—designing scalable data pipelines and analytics-ready datasets while delivering dashboards and analytical models that drive data-informed decisions and operational efficiency.

This position is fully remote and requires a Public Trust (or the ability to obtain it). US citizenship required. The candidate may be required to work outside of business hours, including weekends, based on need.

Key Responsibilities

• Design, build, and maintain automated, scalable ETL/ELT data pipelines using Python, SQL, and cloud-based tools to integrate, transform, and validate structured and unstructured data from diverse sources.
• Develop and manage analytics-ready data models and workflows (e.g., in Databricks or similar platforms) to support reporting, self-service analytics, and advanced data science use cases.
• Implement CI/CD practices using GitLab for data workflows, ensuring reliable, versioned, and repeatable analytics and data engineering processes.
• Design, develop, and deploy interactive dashboards and reports using Tableau, Power BI, or similar tools to deliver complex analysis and actionable insights to business and technical stakeholders.
• Perform data mining, cleaning, and manipulation using SQL and Python (e.g., Pandas, NumPy) to support statistical analyses, visualizations, and decision-support tools.
• Conduct end-to-end analytical and modeling work, including exploratory data analysis, feature preparation, model validation, and documentation; experience with AI or predictive modeling is a plus.
• Collaborate with cross-functional teams (data engineers, analysts, software developers, and stakeholders) to translate business requirements into effective data models, pipelines, and visualizations.
• Compile and maintain metadata, data dictionaries, and technical documentation; produce recurring and ad-hoc reports for leadership.
• Respond to urgent and ad-hoc data requests and support collaborative research and analysis projects across program areas.
• Provide technical guidance and mentorship on analytics best practices, Python scripting, data modeling, and workflow automation.

Required Qualifications

• Bachelor’s degree in data science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, with 5+ years of experience (or 3+ years with a Master’s) in analytics engineering, data engineering, or data analysis.
• Strong proficiency in Python, SQL, Git/GitLab, and experience building ETL/ELT pipelines with CI/CD and data engineering best practices.
• Experience working with relational and non-relational databases (e.g., Oracle, PostgreSQL) and creating executive-ready dashboards using Tableau or Power BI.
• Strong analytical and problem-solving skills, attention to detail, and the ability to analyze large, complex datasets and communicate insights to technical and non-technical stakeholders.
• Ability to work independently and collaboratively in fast-paced, agile environments with excellent written and verbal communication skills.

Preferred Qualifications

• Experience with Databricks, cloud platforms (especially AWS), and modern data infrastructure.
• Exposure to AI/ML, advanced data modeling (classification, forecasting, NLP), and MLOps practices.
• Familiarity with workflow orchestration and automation tools such as Airflow, MLflow, or similar platforms.
• Experience working with government or regulated data environments, Agile/Scrum methodologies, and project management tools like Jira.
• Experience mentoring junior data professionals and contributing to analytics standards, best practices, and team development.

The likely salary range for this position is $127,500 - $172,500. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours

40

Travel Required

None

Telecommuting Options

Remote

Work Location

Any Location / Remote

Total Rewards At GDIT

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee’s date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

Our Identity Verification Process

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

About Our Work

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.

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Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans