Analytics Engineer

About this role

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

T elecommuting Options: Remote

Work Location: Any Location / Remote

Additional Work Locations:

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 Re

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