Principal Analytics Engineer

We are seeking a Principal Analytics Engineer to provide 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.

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 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 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.
• Collaborate with cross-functional teams to translate business requirements into effective data models, pipelines, and visualizations.
• Compile and maintain metadata, data dictionaries, and technical documentation.
• 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 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 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, and modern data infrastructure.
• Exposure to AI/ML, advanced data modeling, 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.

Benefits

• Medical plan options, some with Health Savings Accounts
• Dental plan options
• Vision plan
• 401(k) plan with company match
• Flexible work arrangements
• Paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave
• Short and long-term disability benefits
• Life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance