Analytics Engineer

The Senior Analytics Engineer will deliver advanced analytics and data engineering support across multiple business and program areas, with a focus on scalable pipelines, analytics-ready datasets, and decision-support outputs that improve operational efficiency.

Role Responsibilities

• Design, build, and maintain automated, scalable ETL/ELT pipelines using Python, SQL, and cloud-based tooling to integrate, transform, and validate structured and unstructured data from multiple sources.
• 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 using GitLab to ensure analytics and data engineering processes are reliable, versioned, and repeatable.
• Create interactive dashboards and reports using Tableau, Power BI, or comparable tools to deliver complex analysis to business and technical stakeholders.
• Perform data mining, cleaning, and manipulation using SQL and Python (for example, Pandas and NumPy) to support statistical analysis, visualization, and decision-support tooling.
• Lead end-to-end analytical and modeling activities including exploratory data analysis, feature preparation, model validation, and documentation, with experience in AI or predictive modeling considered a plus.
• Partner with cross-functional teams including data engineers, analysts, software developers, and stakeholders to translate business requirements into data models, pipelines, and visualizations.
• Compile and maintain metadata, data dictionaries, and technical documentation, and produce recurring and ad-hoc reporting for leadership.
• Address urgent and ad-hoc data requests and support collaborative research and analysis efforts across program areas.
• Provide technical guidance and mentorship focused on analytics best practices, Python scripting, data modeling, and workflow automation.

Required Qualifications

• Bachelor’s degree in a 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 and SQL, with demonstrated experience using Git/GitLab and applying CI/CD and data engineering best practices for ETL/ELT.
• Experience with both relational and non-relational databases (for example, Oracle and PostgreSQL) and the ability to produce executive-ready dashboards using Tableau or Power BI.
• Strong analytical and problem-solving skills, attention to detail, and the ability to work with large, complex datasets while communicating insights to technical and non-technical stakeholders.
• Ability to work independently and collaboratively in fast-paced, agile environments, with strong written and verbal communication skills.
• Fully remote role requiring Public Trust (or ability to obtain it), with U.S. citizenship required.

Technologies

• Python, SQL, GitLab, Git
• Tableau, Power BI, Databricks
• Pandas, NumPy
• Airflow, MLflow
• Oracle, PostgreSQL
• AWS
• CI/CD, ETL, ELT

Key Skills for Success

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

Location and Work Requirements

• Location: Remote
• 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)

Salary Range

The likely salary range for this position is USD 127,500 - 172,500 per year.

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