Analytics Engineer
Nitrogen is revolutionizing how financial advisors engage with their clients through AI-powered solutions. As an Analytics Engineer, you will build data workflows and analytics products, ensuring data correctness and reliability while contributing to the overall mission of empowering clients in their investment journey.
Responsibilities
- Builds SQL-based transformation workflows that parse, cleanse, and model complex data with accuracy and resilience within established patterns and standards
- Writes and maintains production-ready dbt models in Snowflake, including tests and documentation appropriate to the change
- Contributes Python workflows that complement SQL/dbt transformations and automate repeatable data tasks
- Supports the successful delivery of daily financial data feeds that standardize raw data from numerous sources into our warehouse
- Supports exports of fresh, correct datasets to downstream production systems, validating outputs and surfacing issues early
- Resolves data issues through analysis and lineage tracing, escalating with clear evidence and proposed fixes when needed
- Delivers high-quality features that meet expectations for correctness, maintainability, and operational safety
- Develops a working understanding of domain-specific custodial data and how it affects customer experience and product behavior
- Uses AI-assisted development tools effectively to increase productivity and code quality (we use Devin and Cursor heavily)
- Demonstrates continuous improvement in independence, throughput, and quality across delivery cycles
- Ensures day-to-day technical contributions align with team priorities and company objectives
Skills
- Experience. You bring early-career experience building data pipelines, analytics workflows, or production data systems, or equivalent hands-on academic or project experience that demonstrates production-grade habits. Experience may come from dedicated data roles or meaningful data ownership within full stack teams
- Applied Experience. This role requires substantial practical experience working with real datasets. Coursework alone is not sufficient
- Data Engineering. You write clear, correct SQL in Snowflake/dbt and can work effectively within an established warehouse architecture. You implement joins, aggregations, and window functions appropriately, and you can extend existing pipelines safely
- Analytical Rigor. You can reason about what “correct” data should look like, validate outputs against business expectations, and explain discrepancies clearly
- Data Investigation. You can trace data lineage across models and sources, narrow hypotheses, and identify root causes and collaborate with senior engineers when broader architectural changes are required. You communicate findings with evidence and propose practical fixes
- AI Tools. You adopt modern AI developer tools to accelerate delivery and improve quality. If your prior exposure is light, you ramp quickly and use them responsibly in production workflows
- Continuous Improvement. You incorporate feedback, strengthen engineering habits, and improve reliability of your work over time. You seek ways to reduce recurring issues through better tests, documentation, and automation
Benefits
- 4% 401(k) Match.
- Free Financial Planning Services.
- Medical, Dental & Vision insurance plans.
- Health Savings Accounts (HSA) or Flexible Spending Accounts (FSA) available depending on chosen medical plan.
- Generous maternity & paternity leave for either the birth or adoption of a child.
- Discounted pet insurance available.
- 3 weeks vacation & 1 week sick time per year.
- 11 paid company holidays per year.
- Remote & in-person team building activities help our employees stay connected and engaged.
- Company wide meetings held by our CEO benefit all employees by keeping everyone in the loop.
- Employee development is our priority.
Company Overview