Senior Business Intelligence Engineer Jobs
Senior Business Intelligence Engineer jobs are open across technology, finance, healthcare, and retail, from mid-level to staff and principal, with specializations in data modeling, dashboard architecture, and pipeline engineering. Find a role that fits from the openings below and apply directly.
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Who We Are
Imprint is building a platform that helps the world’s best brands grow the lifetime value of their customers. We started with co-branded credit cards and rebuilt them to be smarter, more rewarding, and brand-first. We partner with companies like Crate & Barrel, Rakuten, Booking.com, H-E-B, Fetch, and Shell to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. But the card is just the beginning. We combine advanced payments infrastructure, intelligent underwriting, and deep customer data to predict what each customer will do next and act on it, so brands can offer powerful financial products without becoming a bank.
Co-branded cards alone account for over $300 billion in U.S. annual spend, and most still run on legacy bank rails. Imprint is the modern alternative: flexible, embeddable, and built for how people actually pay today. Backed by Kleiner Perkins, Thrive Capital, Ribbit, and Khosla Ventures, we’re building a world-class team to redefine how people pay and how brands grow. If you want to move fast, solve hard problems, and own real outcomes, we want to meet you.
As a Senior BI Engineer, you will own the design, development, and delivery of data products that power business decisions across Imprint. This is a high-impact individual contributor role embedded at the intersection of data engineering and analytics — with AI as a core multiplier in how you work.
You will partner closely with teams across Engineering, Product, Finance, Marketing, and Operations to translate complex business questions into reliable, performant, and scalable BI solutions — from data modeling and pipeline development to dashboards and self-serve analytics infrastructure. You will leverage AI-assisted development tools (Claude, Codex, Cursor, etc.) to accelerate implementation, allowing you to focus your energy on the strategic thinking, problem framing, and stakeholder partnership that AI cannot replace.
This role blends technical depth with strong business judgment, and is best suited for someone who can move fluidly between writing production-grade SQL, architecting semantic layers, and sitting in a room with stakeholders to define what "good" looks like.
What Success Looks Like in the First 90 Days
- Delivered at least one high-priority BI initiative end-to-end, from data model to stakeholder-facing dashboard
- Built strong working relationships with key cross-functional stakeholders to understand data needs and priorities
- Identified and addressed at least one significant gap in data reliability, model coverage, or reporting fidelity
- Established or meaningfully improved documentation and discoverability standards for existing BI assets
- Demonstrated effective use of AI-assisted workflows to accelerate delivery — using AI for implementation (SQL generation, model scaffolding, documentation) while applying human judgment to design, scoping, and quality assurance
- Demonstrated clear judgment in prioritizing requests based on business impact and technical feasibility
Responsibilities
- Design, build, and maintain scalable data models, semantic layers, and data visualizations that serve business-critical reporting needs
- Partner with stakeholders across Engineering, Product, Finance, Marketing, and Operations to understand data requirements and translate them into reliable data solutions
- Own data quality, documentation, and governance practices for BI assets — ensuring dashboards and models are accurate, trustworthy, and maintainable
- Build and maintain dbt models to support consistent, reusable data definitions
- Leverage AI-assisted development tools to accelerate model development, dashboard scaffolding, and documentation — treating AI as a productivity multiplier while owning the analytical design and validation
- Develop and enforce best practices for data model development, such as naming conventions and testing standards
- Identify and resolve performance bottlenecks in queries, pipelines, and reporting layers
- Enable self-serve analytics by building machine-legible, intuitive data products that reduce ad hoc request volume
- Use data to surface insights proactively — not just respond to requests, but identify gaps and opportunities in the business
- Continuously evaluate and adopt emerging AI tooling to improve team velocity — contribute to defining how the BI team integrates AI into its standard workflows
- Contribute to the broader data team's roadmap, tooling decisions, and infrastructure
Qualifications
Required
- Demonstrated experience designing and delivering production-grade solutions in a complex, high-scale data environment
- Deep proficiency in SQL and data modeling Strong SQL comprehension and data modeling skills — ability to read, validate, and direct complex queries is more important than raw writing speed given AI-assisted workflows
- Experience with a modern data stack (e.g. Snowflake/Databricks, dbt, Sigma/Looker, etc.)
- Strong ability to work directly with stakeholders — translating ambiguous business questions into clear, scoped data solutions
- Track record of building data products that are adopted and trusted by non-technical users
- Demonstrated experience building with AI tools (Claude, Codex, Copilot, Cursor, or similar) — not just awareness, but active integration into daily analytical and engineering workflows
Nice to Have
- Experience in fintech, payments, lending, or regulated financial environments
- Familiarity with data orchestration tools (e.g., Airflow)
- Experience building or scaling BI infrastructure in a high-growth startup environment
- Experience defining or implementing AI-augmented analytics workflows at a team level — e.g., AI-assisted code review, automated documentation, prompt-driven data exploration
- Familiarity with agentic AI patterns (MCP, tool-use, context management) and how they apply to data workflows
- Exposure to Python or other scripting languages for data transformation or automation
- Track record of establishing BI governance or data quality frameworks from the ground up
Perks & Benefits
- Competitive compensation and equity packages
- Leading configured work computers of your choice
- Flexible paid time off
- Fully covered, high-quality healthcare, including fully covered dependent coverage
- Additional health coverage includes access to One Medical and the option to enroll in an FSA
- 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents
- Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity
Imprint is committed to a diverse and inclusive workplace. Imprint is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Imprint welcomes talented individuals from all backgrounds who want to build the future of payments and rewards. If you are passionate about FinTech and eager to grow, let’s move the world forward, together.
Compensation Range: $170K - $210K
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Find JobsSenior Business Intelligence Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Amazon9

- Walmart8

- Cornerstone Research7

- Intuit7

- Capgemini6

Top Industries Hiring
- Technology & Software62
- Consulting & Professional Services19
- Retail14
- Healthcare & Medical Services11
- Banking & Financial Services9
What Employers Look For
The qualifications that appear most often in senior business intelligence engineer jobs.
- Five or more years of experience in business intelligence, data analytics, or data engineering roles
- Advanced SQL proficiency including window functions, CTEs, and query optimization
- Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift
- Proficiency with at least one BI visualization tool such as Tableau, Looker, or Power BI
- Experience with data modeling methodologies and tools including dbt or similar transformation frameworks
- Bachelor's degree in computer science, information systems, statistics, or a related quantitative field
Tips for Your Senior Business Intelligence Engineer Job Search
Tailor your resume to BI stack specifics
Generic data engineering resumes lose out. List the exact tools each employer uses, whether that's dbt, Looker, Snowflake, or Power BI, and quantify the scale of the data you worked with, such as row counts, refresh cadences, or dashboard user counts.
Highlight cross-functional stakeholder work
Senior BI roles require translating ambiguous business questions into structured data products. Show concrete examples where you worked directly with finance, marketing, or product teams to define KPIs, not just build what you were handed.
Apply early to roles that fit
Migrate Mate lists senior business intelligence engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by your modeling approach
Some teams use Kimball dimensional modeling, others prefer OBT or activity schema patterns. Read job descriptions for clues about modeling philosophy before applying, because misalignment on this point surfaces in technical screens and causes real friction.
Prepare a take-home or live SQL case study
Most senior BI interviews include a SQL or data modeling exercise. Practice writing window functions, CTEs, and incremental model logic under time pressure, and be ready to explain your query choices out loud rather than just producing correct output.
Negotiate scope and tooling before accepting
Before signing, ask whether the team has established semantic layer ownership, data governance processes, and tool standardization. Joining a team mid-migration between tools or without clear BI ownership adds months of uncompensated technical debt work.
Senior Business Intelligence Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most senior business intelligence engineers?
The companies hiring the most senior business intelligence engineers right now include Amazon, Walmart, and Cornerstone Research, with the largest share of openings in California, New York, and Washington, based on current listings on Migrate Mate as of June 2026. Demand is concentrated at companies managing large-scale transactional or customer data across technology, financial services, and healthcare verticals.
How many senior business intelligence engineer jobs are remote?
About 32% of senior business intelligence engineer openings are fully remote or hybrid as of June 2026, reflecting strong demand for distributed data teams across the industry. Roles focused on cloud-native BI stack ownership and self-serve analytics platform development tend to offer the highest proportion of fully remote arrangements.
How do you become a senior business intelligence engineer?
Most senior business intelligence engineers start as analysts or junior data engineers, then build depth in SQL, cloud warehousing, and a major BI visualization tool over several years. Moving up requires owning end-to-end data products, not just fulfilling requests, and demonstrating that you can define data models and govern metric definitions independently. Earning a dbt certification or a cloud platform credential helps signal technical seniority to hiring teams.
Can you get hired as a senior business intelligence engineer without direct senior-level experience?
You can make a case for a senior role without an explicit senior title if you can show that you owned critical data infrastructure or led a BI migration project rather than contributing to one. Hiring managers weigh the complexity and business impact of your past work over job titles. A strong take-home exercise demonstrating advanced modeling and documentation practices can close gaps that a resume alone cannot.
What does the senior business intelligence engineer interview process look like?
Most processes run three to four rounds. An initial recruiter screen is followed by a technical phone interview covering SQL and data modeling concepts, then a take-home or live coding exercise involving schema design or dashboard architecture. Final rounds typically include a stakeholder or cross-functional panel where you walk through past projects and explain how you handled ambiguous or conflicting data requirements from business partners.
Where can I find and apply to senior business intelligence engineer jobs?
You can find and apply to senior business intelligence engineer jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your stack and experience level, then apply directly to each one that fits.
See All 190+ Senior Business Intelligence Engineer Jobs
Jump back to the full list of openings and apply to any senior business intelligence engineer role that fits.
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