Job Closed
This listing is no longer active.
The growth platform for wealth management firms. Makers of Riskalyze since 2011.
Analytics Engineer
Location
United States
Posted
97 days ago
Salary
$100K - $115K / year
Seniority
Senior
Job Description
Analytics Engineer
Nitrogen
• 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.
Job Requirements
- 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. Our employees invest so much in our company and we love getting to invest in them. The company will match your contributions dollar-for-dollar, up to 4% of your total annual compensation.
- Free Financial Planning Services. By working at a financial technology company, you get the benefit of fantastic financial advice. This is offered to all employees wanting expert guidance on how to handle their money.
- Medical, Dental & Vision insurance plans. We want to help keep you (and your family) healthy! Comprehensive health insurance options for you & your family.
- Health Savings Accounts (HSA) or Flexible Spending Accounts (FSA) available depending on chosen medical plan. We know that investment risk isn’t a one-size-fits all and neither are your health savings options!
- Generous maternity & paternity leave for either the birth or adoption of a child. Mom's & Dad's need time with their new family members!
- Discounted pet insurance available. Pets are family too!!
- 3 weeks vacation & 1 week sick time per year.Take the time you need for fun or simply time to recover from not feeling well.
- 11 paid company holidays per year. Enjoy your time off; you deserve it!
- Remote & in-person team building activities help our employees stay connected and engaged. We absolutely love to hype our people up!
- Company wide meetings held by our CEO benefit all employees by keeping everyone in the loop. We are one team, and we tackle projects together.
- Employee development is our priority. From leadership training, to mentorship, to industry resources, we care about progressing you in your career.
Related Guides
Related Categories
Related Job Pages
More Analytics Engineer Jobs
Senior Data Analytics Engineer
SysdigConfidently secure containers, Kubernetes and cloud services with #SecureDevOps.
• You will report to the Director, Analytics and AI Transformation. • Partner directly with business stakeholders to identify core challenges, define key performance indicators (KPIs), and translate high-level needs into structured technical plans. • Own the full analytics workflow, from transforming raw data in dbt to building dashboards in Sigma and presenting findings that influence strategy • Write SQL to solve complex modeling challenges and maintain a "single source of truth" across the organization. • Deliver high-impact, data-driven insights and recommendations; collaborate with leadership to influence key decisions and optimize the growth funnel • Help shape data governance and foster data literacy, empowering stakeholders to self-serve with accurate data
Analytics Engineer
NcontractsRisk management and compliance software purpose built for financial services organizations.
Analytics Engineer Remote | Product and Development | Full-Time WHO WE ARE Headquartered in Nashville, Tenn., Ncontracts leads the industry in integrated risk management and compliance solutions, serving over 5,000 financial institutions nationwide. As a seven-time Inc. 5000 Fastest Growing Companies honoree and consistent year-over-year recipient of "Best Places to Work" awards, we offer a thriving, work environment where career growth and life-work balance go hand in hand. At Ncontracts, you'll join a team of industry experts dedicated to strengthening the financial services sector through innovation and thought leadership. We're seeking creative, collaborative, and self-driven professionals across all areas of our business - from developing cutting-edge solutions to sales, marketing, customer support, and beyond. Join us in our mission to make the financial industry stronger and more resilient, while advancing your career in a supportive, dynamic environment that values your unique skills and perspectives. THE ROLE We are currently seeking an Analytics Engineer to join our growing team! The Analytics Engineer reports to the Data Architect and is responsible for building the data models and analytical frameworks that drive product improvement across Ncontracts’ suite of risk management and compliance solutions. This role sits at the intersection of data modeling and product analytics. You’ll own the transformation and presentation layers that turn raw product data into actionable insights, working closely with engineering and product teams to identify what’s working, what isn’t, and why. You’ll need strong SQL and modeling skills to build reliable, well-tested datasets, and equally strong product intuition to know which metrics actually matter for our financial institution customers. Our modern data stack includes Snowflake as our cloud data warehouse, dbt for data transformation and modeling, and Sigma for business intelligence and visualization. You’ll own the modeling layer end-to-end—designing well-structured, documented, and tested datasets that power decisions across the organization. This role will have a direct impact on our customers and our brand. You’ll deliver the next generation of customer-facing reporting, dashboards, and data products that elevate the Ncontracts experience and set a new standard for how financial institutions interact with their data. We’re looking for candidates who are curious, resourceful, and genuinely excited about AI—whether that’s using it to streamline their own workflows, finding smarter ways to validate data, or simply staying on top of how the landscape is evolving. You don’t need to be an ML engineer, but we want someone who leans into new tools and approaches rather than waiting to be told to use them. YOU WILL - 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 - Design instrumentation strategies with engineering teams to ensure we’re capturing the right signals from Ncontracts’ product suite - 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 YOU BRING (Qualifications) Technical Foundation - 5+ years of experience in analytics engineering, data analytics, or a related data role with demonstrated technical expertise - Strong 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 BONUS POINTS (Preferred Qualifications) - Knowledge of financial services data domains such as lending, compliance, risk management, or regulatory reporting - Background in high-volume event data, behavioral analytics, or product telemetry systems - Exposure to funnel analysis, cohort analysis, or experimentation frameworks (A/B testing) - Understanding of software system architectures and how they generate telemetry - Enthusiasm for 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 - Experience 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 - dbt Analytics Engineering Certification or SnowPro certification - Familiarity with reverse ETL tools (Census, Hightouch) for activating data in operational systems - Contributions to open-source data or analytics projects WE OFFER - A fun, fast-paced work environment - 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 - 2 Paid Volunteer Time Off Days - And much more! Compensation Information Pursuant to state and local law disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience and location is $120,000 to $160,000 per year. This position may be eligible for an annual discretionary incentive award. The incentive award amount is dependent upon company performance and your personal performance and is not guaranteed. 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. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Other Duties Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
Staff Analytics Engineer
BoulevardBoulevard powers the next generation of salons and spas so it’s easier for everyone to look and feel their best.
• Architect and lead the analytics foundation powering Boulevard’s data ecosystem and products. • Own analytical platform, data visualization, and advanced machine learning capabilities. • Drive complex, high-impact data initiatives that enhance product performance and customer experience. • Partner with Product, Engineering, and Analytics teams for collaborative initiatives and data-driven experiences. • Deliver robust customer-facing reporting, dashboards, and analytics features.
• Develop a strong understanding of core electrical and mechanical system principles • Conduct data analysis with Python to drive informed business decisions • Apply statistical methods to assess data completeness, accuracy, and reliability • Support engineering teams with root cause analysis investigations • Promote the adoption of semantic models and ontologies across the organization • Design and build executable Python-based analytical models • Automate data processing, analysis, and formatting workflows • Clean, structure, and analyze datasets using Python • Organize data and implement standardized labeling practices in AWS S3 • Deploy machine learning algorithms on both numerical and categorical data sets




