Analytics Engineer

General Dynamics Information Technology, Inc.

$127K — $172K *
US-AnywhereRemote in United States
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor’s degree in a quantitative field (data science, computer science, etc.)
  • 5+ years of experience in analytics or data engineering (or 3+ years with a Master's)
  • Proficiency in Python, SQL, and Git/GitLab
  • Experience creating ETL/ELT pipelines and dashboards using Tableau or Power BI
  • Strong analytical skills with attention to detail and effective communication ability

Responsibilities

  • Design, build, and maintain automated data pipelines using Python and SQL
  • Develop and manage analytics-ready data models for reporting and self-service analytics
  • Implement CI/CD practices using GitLab for data workflows
  • Create interactive dashboards with tools like Tableau to provide insights
  • Perform data cleaning and manipulation for statistical analyses
  • Conduct end-to-end analytical work, including exploratory analysis and model validation
  • Collaborate with cross-functional teams to meet data requirements

Benefits

  • Remote work flexibility without the need for relocation
  • Ability to work with advanced analytics and data engineering practices
  • Engage with cross-functional teams and stakeholders
  • Opportunity for mentorship and professional development
Full 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

Job Qualifications:

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

Job Description:

The Senior 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

Additional Work Locations:

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