WHAT WE DONitrogen has been revolutionizing how financial advisors and wealth management firms engage with their clients since the launch of Riskalyze in 2011. Today, Nitrogen offers an integrated client engagement software platform featuring risk tolerance, proposal generation, investment research, and financial planning tools designed to help firms and financial advisors deliver personalized advice. We invented the Risk Number®, built on top of a Nobel Prize-winning academic framework, and are the champions of the Fearless Investing Movement — tens of thousands of financial advisors are committed to our mission of empowering the world to invest fearlessly.Nitrogen is an equal opportunity employer. We encourage people from underrepresented groups to apply. We are committed to being fair and intentional in our hiring decisions by reviewing every application thoroughly.THE TEAMOur Data and Services Team empowers the world to invest fearlessly by building robust data pipelines and products that power advisors and their firms across the wealth management industry.WHAT YOU’LL BE WORKING ONAs a Staff Analytics Engineer on the Data &amp; Services team, you’ll be building production data workflows and analytics products for our customers. This is a hybrid role, combining engineering rigor and an analyst’s deep understanding of the data. You’ll be a lead voice for data correctness, ensuring data integrity and a high level of trust in our data pipeline results. The Staff Analytics Engineer:<ul> <li>Builds SQL-based transformation workflows that parse, cleanse, and model complex data with accuracy and resilience.</li> <li>Owns the successful delivery of daily financial data feeds that standardize raw data from numerous sources into our warehouse, and export fresh datasets out to production systems.</li> <li>Resolves customer impacting problems through deep analysis, tracing through the data lineage and using your domain knowledge to intuit the cause and solution.</li> <li>Builds customer-facing data insights products through advanced SQL modeling or machine learning models when appropriate.</li> <li>Delivers high-quality, production-grade features, and reliably meets commitments.</li> <li>Maintains a deep understanding of what our domain-specific data means to our customers and their product experience.</li> <li>Sets a high bar for technical productivity and efficiency through expert use of AI and cutting-edge tools.</li> <li>Proactively identifies and addresses technical debt and developer experience needs, and advocates for AI-enhanced solutions where appropriate.</li> <li>Demonstrates a continuous improvement mindset in both personal development and all technical workflows.</li> <li>Ensures your technical contributions align with company objectives and expectations.</li> </ul><ul> <li> Experience. You bring 5+ years of hands-on experience in data engineering, building reliable pipelines and production-grade workflows.</li> <li> Data Engineering. You’re an expert hand at writing optimized SQL &amp; Python in Snowflake &amp; dbt. You have seen it all when it comes to data parsing and cleansing bad data, and production-grade workflow design is second nature.</li> <li> Analytical Rigor. You have a business-savvy mindset, able to understand what the data means, and able to quickly diagnose how it should look and why it’s wrong.</li> <li> Data Investigation. You’re a master data sleuth, able to trace data lineages and quickly identify a root cause. You’re extremely comfortable navigating both deep technical topics and customer impact.</li> <li> AI Tools. You’re rapidly adopting the latest in Agentic AI developer tools to supercharge your productivity and impact. If your prior exposure in this area is light, get ready to buckle up and dive in! We use Devin and Cursor heavily here, and are always looking for the best of breed tools for our teams.</li> <li> Machine Learning. Experience with ML algorithms and ML engineering pipelines is a major plus. Were building toward an exciting future of data insight products that leverage our vast market data in wealth management.</li> </ul>The expected compensation range for this role is a $140k-$160k.Lesser experience may result in lower compensation and greater experience may result in greater compensation than the stated range.