Staff Data Engineer

Remote from: USA
Salary, yearly, USD: 160,000 - 207,400
Department: Data Science & Analytics
Employment type: Full Time,
Job posted: 17 Jun 2026
Apply before: 17 Jul 2026
Experience level: Senior
Views / Applies: 76 / 10

Powering the Next Generation of Premium Salons and Spas.

Computer Software
2016

AI Summary

Boulevard is hiring a Staff Data Engineer to architect and lead the data foundation powering their client experience platform for self-care businesses. This senior role involves owning the data platform, visualization, machine learning capabilities, and enabling data-driven products and decision-making. The engineer will collaborate cross-functionally on customer-facing data products, Snowflake data sharing, visualization optimization, and AI innovation. Key projects include delivering robust analytics features, designing secure data sharing solutions, and deploying ML for recommendations and forecasting. This position requires extensive expertise in data architecture, analytics engineering, and practical machine learning applications.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight This is a senior staff-level role requiring deep expertise in data architecture, machine learning, and analytics engineering. The complexity and impact of the position justify a difficulty level of 4.

Salary Analysis

AI Insight The offered salary of $183,700 (median) is competitive within the US market, aligning with the 50th-75th percentile for a Staff Data Engineer role. The range of $160,000-$207,400 reflects the company's commitment to attracting top talent in a high-demand field.

Key Skills

Data Engineering Snowflake Machine Learning Data Architecture Analytics Engineering Python SQL ETL Cloud Computing Data Modeling

Cover Letter Sample

Dear Hiring Manager,

I am writing to express my strong interest in the Staff Data Engineer position at Boulevard. With over 8 years of experience in data engineering and architecture, I have a proven track record of building scalable data platforms that drive business insights and AI innovation. At my previous role, I led the design of a Snowflake-based data warehouse that improved query performance by 60% and enabled real-time analytics.

I am particularly drawn to Boulevard's mission to empower self-care businesses with a modern client experience platform. I have extensive experience collaborating with cross-functional teams to deliver data products that enhance customer experiences. My expertise in machine learning and data modeling aligns perfectly with the key projects outlined, such as customer-facing data products and data sharing solutions.

I am excited about the opportunity to contribute to Boulevard's data foundation and look forward to the possibility of discussing how my skills can benefit your team.

Sincerely, [Your Name]

Possible Interview Questions

Describe your experience designing and building a scalable data platform. What architectural decisions did you make, and how did you ensure performance and reliability?

At my last company, I led the redesign of our data warehouse from a legacy Redshift setup to Snowflake. We adopted a medallion architecture (bronze, silver, gold) to separate raw, cleaned, and aggregated layers. I implemented automated data quality checks using dbt, and we used Airflow for orchestration. To ensure performance, we optimized clustering keys and materialized views for frequent queries, resulting in a 50% reduction in query latency. Reliability was achieved through multi-cluster warehouses and cross-region replication for disaster recovery.

How would you approach building a customer-facing analytics dashboard that needs to handle real-time or near-real-time data?

I would first clarify the latency requirements and data volume with stakeholders. For near-real-time, I'd use streaming ingestion via Kafka or Snowpipe into Snowflake, then create materialized views or aggregates for dashboard queries. The dashboard layer would use a cloud-native BI tool like Tableau or Looker, optimized with pre-aggregated data and caching. I'd implement row-level security to ensure customers only see their data. Performance testing with realistic data volumes would be critical to ensure sub-second query response times.

Explain the concept of data sharing in Snowflake and how you would design a secure data sharing solution for external customers.

Snowflake data sharing allows you to share live data with other Snowflake accounts without copying or moving data. For external customers, I would create a dedicated reader account for each customer or use a marketplace listing with controlled access. I'd design secure views that limit data to only the customer's slice, using row-level access policies. I'd also implement automated provisioning scripts via Snowflake's SQL API to manage reader accounts and grants. Auditing via Snowflake's access history ensures compliance.

Describe a machine learning project you deployed in production. How did you handle feature engineering, model selection, and monitoring?

I built a churn prediction model for a SaaS product. Features were engineered from user activity logs and billing data using Snowflake SQL and Python. We used gradient boosting (XGBoost) for its interpretability and performance. The model was deployed as a REST API via a containerized service on AWS ECS, with predictions stored in Snowflake for downstream dashboards. Monitoring included data drift detection on features using custom metrics, and we retrained the model monthly. We also set up alerts for prediction confidence drops.

How do you ensure data quality and consistency in a data platform with multiple data sources and consumers?

I implement a multi-layered data quality framework. First, during ingestion, we run validation checks (nulls, duplicates, schema conformity) and quarantine bad records. In the transformation layer (e.g., dbt), we enforce tests for uniqueness, referential integrity, and business rules. We also maintain a data catalog with lineage tracking using tools like Atlan or Alation. For consumers, we publish service-level agreements (SLAs) for data freshness and accuracy, monitored via dashboards. Regular data audits and feedback loops with data owners help catch issues early.

Who is Boulevard?

Boulevard provides the first and only client experience platform for appointment-based, self-care businesses. We empower our customers to give their clients more of the magical moments that matter most.

Before launching in 2016, our founders spent months interviewing salon managers and working behind front desks to understand their pain points so we could design a modern, user-friendly platform that meets the unique needs of their business. Our roots may be in hair salons, but we are built for the broader self-care industry, including many types of salons, spas, medspa, barbershops, and more. Our technology not only helps our customers survive but thrive. Take a look at how we (and YOU) can make that happen.

We have an insatiable curiosity and embrace experimentation. We believe that simple solutions require the most sophistication, and we design each and every detail to maximize potential, power, and impact. Do our values match? Read through our story and what we value the most.

Our team values and celebrates our diverse backgrounds. Being open about who we are and what we do allows us to do the best work of our lives. We believe in equal opportunity for all, and you should too.

Come do the best work of your life at Boulevard.

We’re hiring a Staff Data Engineer to architect and lead the data foundation powering Boulevard’s data products. In this role, you’ll own our data platform, visualization, advanced machine learning capabilities, and the systems that enable data-driven products and decision-making across the company.

Reporting to the Director of Data Engineering, you’ll play a critical role in architecting, designing, developing, and maintaining the data ecosystems and analytics capabilities that power customer-facing products. You’ll drive complex, high-impact data initiatives that enhance product performance and customer experience through actionable insights and robust analytical frameworks. This senior technical role demands extensive expertise in data architecture, analytics engineering, and practical machine learning applications.

Domains of Ownership

Data Architecture – Design, build, and maintain foundational data models that serve as the single source of truth for analytics across both internal and external stakeholders.
Cross-Functional Collaboration – Partner with Product, Engineering, and Analytics teams to scope and deliver new initiatives, develop analytics features, and create data-driven customer experiences.
Scalable Data Products – Develop frameworks, tools, and workflows that enhance efficiency and scalability, ensuring high standards of data quality, consistency, and performance.
AI Innovation & Actionable Insights – Translate business requirements into scalable data models, dashboards, and analytical tools. Proactively identify opportunities for anomaly detection, predictive analytics, recommendations, forecasting, and AI-driven innovation.Impact-Focused Solutions – Leverage modern analytics and development tools to deliver measurable business value quickly—while maintaining long-term scalability and maintainability.

Key Projects & Initiatives

Customer-facing Data Products: Collaborate with Product Management and Engineering to deliver robust customer-facing reporting, dashboards, and analytics features.
Snowflake Data Sharing – Design and implement secure, performant Snowflake data sharing solutions that empower customers to access and leverage data safely and efficiently.
Data Visualization & Performance Optimization – Oversee data visualization platforms, optimizing data models and query performance to deliver fast, reliable, and intuitive analytics experiences.
Machine Learning & AI Innovation – Develop and deploy machine learning solutions for recommendations, forecasting, anomaly detection, and predictive insights that enhance product intelligence.

What You’ll Do Here

Technical Architecture – Lead complex data initiatives by transforming ambiguous business needs into scalable architectures, pipelines, and analytical models that deliver impact.
Cross-Functional Collaboration: Partner with Product Management, Product Engineering, and Analytics to understand requirements and deliver analytics platform capabilities for both external and internal stakeholders.
Data Modeling & Design: Drive key semantic modeling design decisions that balance current reporting needs with future scalability and adaptability.

What You’ll Need to Thrive

Bachelor’s degree or higher in Computer Science, Information Technology, Data Science, or a related discipline
7+ years of professional experience in Data Engineering
Proven track record of delivering data products, data platform capabilities in partnership with Product teams
Deep expertise with modern data stack technologies: DBT, Snowflake, SQL, Python, and BI tools like Looker/Omni.
Strong understanding of modular and reusable data modeling best practices (e.g., star and snowflake schema design)
Comprehensive knowledge of data governance, data quality frameworks, and analytics/security best practices
Excellent problem-solving, communication, and cross-functional collaboration skills, with experience working on global teams

How We’ll Take Care of You

At Boulevard, we work hard to structure compensation in a way that balances internal equity with local market competitiveness, and we’re happy to share a good-faith estimate of the base salary range for this role. For candidates in NYC, the SF Bay Area, and Seattle, the anticipated base salary range is $174,500 – $205,000 per year. For all other U.S. locations, the anticipated base salary range is $160,000 – $207,400 per year. In addition to this base compensation, this role may be eligible to participate in a variable compensation program. Final compensation will vary based on a variety of factors which include but are not limited to applicable experience, location, and final leveling.

In addition to the wonderful people you’ll get to work with and challenging projects that’ll push you – Boulevard is here to make sure you’re always at the top of your game emotionally, mentally, and physically.

✨ We’ve got you covered with a 401(k) match plus dental, medical, vision, and life insurance.
🏝 Take a break whenever you need with our flexible vacation day policy.
🖥 Fully remote so you can choose where you want to work. You’ll receive a work from home stipend every month.
💚 Family planning resources and specialized support programs.
🔮 Equity: get ahead on the ground floor and grow with Boulevard.
💅 Boulevard Bucks Learning and Development program allows employees to explore businesses in the market we serve.

📲 We recommend following our official LinkedIn page to stay up to date on all things Boulevard life!

Boulevard Labs, Inc. is an Equal Opportunity Employer committed to hiring a diverse workforce and sustaining an inclusive culture. All employment decisions at Boulevard Labs, Inc. are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

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