Analytics Engineer

About the role

We are currently seeking an Analytics Engineer to join our growing team!

Responsibilities

• Design, build, and maintain the data models in Snowflake using dbt that power product analytics—from raw source data through to business-ready, well-documented datasets
• Define and maintain metrics frameworks and KPIs that drive product and business decisions across the organization
• Build interactive dashboards and self-service reports in Sigma that empower stakeholders to explore data and answer their own questions
• Partner with product managers to translate fuzzy questions (“why is this feature underperforming?”) into precise, answerable analyses
• Conduct deep-dive analyses including funnel analysis, cohort analysis, and root cause investigations to surface product insights
• Own data quality end-to-end, including dbt tests, validation, documentation, and monitoring across all models
• Optimize query performance and warehouse costs in Snowflake through efficient modeling patterns, materialization strategies, and resource monitoring
• Establish and enforce data governance standards, including naming conventions, documentation requirements, and consistent metric definitions to maintain a single source of truth
• Contribute to the evolution of the data platform by evaluating new tools, technologies, and best practices

Requirements

• Technical Foundation: 5+ years of experience in analytics engineering, data analytics, or a related data role with demonstrated technical expertise
• SQL proficiency with experience writing complex queries for data transformation, analysis, and performance optimization
• Hands-on experience with dbt (dbt Core or dbt Cloud), including model design, testing, documentation, and deployment workflows
• Experience working with Snowflake or a comparable cloud data warehouse (BigQuery, Redshift, Databricks)
• Solid understanding of data modeling concepts, including dimensional modeling, slowly changing dimensions, and star/snowflake schemas
• Proficiency with data visualization and BI tools, preferably Sigma, with the ability to create compelling dashboards and reports for diverse audiences
• Understanding of software engineering fundamentals: version control (Git), testing, code review, and CI/CD practices
• Comfort working with semi-structured data (JSON, nested structures)
• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or equivalent practical experience
• Analytical Mindset: Experience building metrics frameworks and defining KPIs that drive product and business decisions
• Track record of error analysis and root cause investigation on product and data quality issues
• Ability to work backwards from business questions to data requirements
• Healthy skepticism about data quality and metric definitions—you ask “should we trust this number?” before building on it
• Product Orientation: Genuine curiosity about how products work and why users behave the way they do
• Experience partnering directly with product and engineering teams in a collaborative, cross-functional environment
• Communication skills to make technical findings accessible to non-technical stakeholders
• Comfort with ambiguity and the ability to iterate toward the right answer rather than waiting for perfect requirements

Skills

• Curiosity about AI and a habit of using AI tools to accelerate your own work—writing code, automating tasks, exploring data, or prototyping solutions
• Experience measuring or evaluating AI-powered product features, including defining success metrics, tracking adoption, or analyzing model performance from a product analytics perspective
• Familiarity with emerging data and workflow patterns, including tracing, observability, and agent-based systems
• Experience with Python for data transformation, scripting, or automation tasks
• Familiarity with data observability platforms (Monte Carlo, Elementary, Soda)
• Knowledge of compliance frameworks relevant to financial services (SOC 2, GLBA, FFIEC)
• Experience implementing data contracts, data mesh, or modern data governance frameworks
• Exposure to orchestration tools such as Airflow, Dagster, or Prefect
• Familiarity with reverse ETL tools (Census, Hightouch) for activating data in operational systems

Benefits

We Offer All Full-time Team Members:

• A fun, fast-paced work environment
• A responsible PTO Plan that meets or exceeds state and local medical and family leave laws
• 11 paid holidays
• Community and social events to keep you connected and engaged
• Mental Health Benefits
• Medical, Dental and Vision insurance
• Company-paid Group Life Insurance, Short- and Long-Term Disability
• Flexible Spending Account & Health Savings Account
• Aflac Benefits – Critical Illness, Cancer Protection, & Hospital Choice
• Pet Insurance
• 401 (k) with company match with eligibility on Day 1 of employment
• And much more!

Part-Time, Temporary, Contractor, and Intern positions are not eligible for company benefits, including paid time off, health insurance, and other employee benefit programs.

AAP/EEO Statement

Ncontracts provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.