Senior Analytics Engineer – Customer Experience Data Engineering & Insight Leadership – Champion Data‑Driven CX Excellence, Operational Intelligence, and Strategic Decision‑Making at brighthush

About brighthush

At brighthush, we’re on a relentless mission to bring clarity to the world’s most complex questions. By transforming collective human intuition into transparent, real‑time probabilities, we empower millions to make informed decisions across politics, economics, sports, culture, and beyond. In 2025 alone, our platform processed over $21 B in trades, and our community continues to grow as we bring truth to the forefront of global conversations.

Our culture is built on transparency, ownership, and impact. We thrive on data‑driven experimentation, rapid iteration, and a relentless focus on delivering value to our users. If you’re passionate about turning raw data into actionable insights that shape user experience and business outcomes, brighthush is the place for you.

Why the Customer Experience (CX) Team Matters

The CX team is the heartbeat of brighthush’s user journey. From managing withdrawals and KYC to resolving market disputes, the team tackles high‑stakes challenges that directly influence user trust and platform reliability. As the data foundation for this critical group, you will play a pivotal role in ensuring that every decision is backed by clean, reliable, and actionable data.

In a world where every interaction counts, the CX team’s ability to respond swiftly to operational challenges can mean the difference between a satisfied user and a lost customer. Your work will empower the team to spot emerging trends, pre‑empt issues, and continuously refine the user experience.

Role Overview

As a Senior Analytics Engineer, you will bridge the gap between raw operational data and the people who use it to make strategic decisions. You will partner with product managers, engineers, and CX leaders to design, build, and maintain the data models, pipelines, and semantic layer that power dashboards, reports, and self‑serve datasets. Your work will enable the CX team to respond quickly to operational challenges, identify trends, and drive continuous improvement.

Beyond the technical stack, you will be a catalyst for data literacy across the organization, translating complex analytics into clear, actionable stories that resonate with stakeholders at all levels.

Key Responsibilities

• Data Architecture & Modeling – Design and evolve robust, scalable data models that capture the full spectrum of CX operations, from user onboarding to dispute resolution.
• Pipeline Development – Build and maintain end‑to‑end data pipelines using modern ETL/ELT tools (e.g., dbt, Airflow, Snowflake) to ingest, cleanse, and transform operational data.
• Semantic Layer & Self‑Serve Enablement – Create intuitive semantic layers and data catalogs that empower product and business teams to query data directly, reducing dependency on engineering.
• Dashboard & Report Ownership – Own the end‑to‑end lifecycle of key CX dashboards (e.g., KYC completion rates, withdrawal velocity, dispute resolution time) in tools such as Looker, Tableau, or Power BI.
• Data Quality & Governance – Implement rigorous data quality checks, lineage tracking, and governance policies to ensure data integrity and compliance with regulatory standards.
• Stakeholder Collaboration – Work closely with CX leaders, product managers, and data scientists to translate business questions into data solutions, and to prioritize feature requests.
• Performance Optimization – Continuously monitor and optimize query performance, storage costs, and pipeline throughput to support real‑time decision making.
• Mentorship & Knowledge Sharing – Mentor junior analytics engineers and data analysts, fostering a culture of learning and technical excellence.
• Innovation & Experimentation – Champion new data technologies, frameworks, and best practices that can accelerate insight delivery and improve user experience.
• Cross‑Functional Leadership – Lead cross‑domain initiatives such as fraud detection, risk analytics, and product recommendation engines, ensuring alignment with business objectives.
• Continuous Improvement – Drive a culture of iterative improvement by conducting post‑mortems, root‑cause analyses, and data‑driven retrospectives.

Essential Qualifications

• 10+ years of experience in data engineering, analytics, or a related field, with at least 5 years in a senior or lead role.
• Proven expertise in designing and maintaining large‑scale data warehouses (Snowflake, BigQuery, Redshift) and data lakes.
• Hands‑on experience with modern ETL/ELT tools (dbt, Airflow, Prefect) and version control (Git).
• Strong SQL skills and familiarity with analytical languages such as Python or R for data manipulation.
• Deep understanding of data modeling concepts (star, snowflake, dimensional modeling) and best practices.
• Experience building and maintaining dashboards in Looker, Tableau, Power BI, or similar BI platforms.
• Solid grasp of data governance, lineage, and quality frameworks.
• Excellent communication skills, with the ability to translate technical concepts to non‑technical stakeholders.
• Demonstrated ability to work in a fast‑paced, high‑impact environment.
• Strong analytical mindset with a passion for uncovering hidden patterns and driving data‑driven decisions.

Preferred Qualifications

• Experience in a fintech or high‑volume transaction environment.
• Knowledge of regulatory compliance frameworks (KYC, AML, GDPR) and how they impact data pipelines.
• Familiarity with cloud platforms (AWS, GCP, Azure) and their data services.
• Background in data science or machine learning, with a focus on predictive modeling for customer experience.
• Experience leading cross‑functional data initiatives and driving adoption of data‑driven culture.
• Published contributions to open‑source data engineering projects or community blogs.

Core Skills & Competencies

• Data Architecture & Engineering
• ETL/ELT Development
• SQL & Analytical Programming
• Business Intelligence & Dashboarding
• Data Governance & Quality
• Stakeholder Management
• Performance Tuning & Optimization
• Mentorship & Team Leadership
• Continuous Learning & Innovation
• Strategic Thinking & Business Acumen

Career Growth & Learning Opportunities

At brighthush, your career path is designed to evolve with your ambitions. As a Senior Analytics Engineer, you will:

• Progress to a Lead Analytics Engineer or Data Engineering Manager role, overseeing a team of engineers and shaping the data strategy.
• Take ownership of cross‑domain data initiatives, such as fraud detection, risk analytics, or product recommendation engines.
• Participate in hackathons, internal data challenges, and industry conferences to stay at the forefront of data technology.
• Access a generous learning stipend for courses, certifications, and workshops in data science, cloud architecture, and leadership.
• Collaborate with senior leaders on strategic projects that directly influence brighthush’s growth trajectory.
• Lead the development of internal knowledge bases and best‑practice guides that become the go‑to resource for the entire organization.
• Earn recognition through our annual “Data Champion” awards and receive opportunities to speak at industry events.

Work Environment & Company Culture

We believe that great data solutions are born in great environments. At brighthush, you’ll experience:

• A fully remote, globally distributed team that values flexibility, trust, and autonomy.
• Transparent communication channels, from weekly all‑hands meetings to open Slack channels.
• A culture of ownership where your ideas are heard, tested, and implemented quickly.
• Regular “data hack days” where teams experiment with new tools and share learnings.
• Inclusive hiring practices and a commitment to diversity, equity, and inclusion.
• Cross‑functional collaboration with product, engineering, finance, and compliance teams.
• Access to a vibrant internal community of data enthusiasts, including meetups, lunch‑and‑learns, and peer‑review sessions.

Diversity, Equity, and Inclusion

At brighthush, we recognize that diverse perspectives drive innovation. We actively foster an environment where every voice is heard, respected, and empowered to contribute. Our hiring practices, mentorship programs, and community initiatives are designed to support underrepresented groups in tech and data science.

Compensation, Perks & Benefits

While specific figures vary by location and experience, brighthush offers a competitive total rewards package that includes:

• Base salary commensurate with market rates for senior data engineering roles.
• Performance‑based bonuses tied to product impact and team success.
• Equity options that allow you to share in the company’s long‑term growth.
• Comprehensive health, dental, and vision insurance for you and your dependents.
• Unlimited paid time off and a flexible work‑from‑home policy.
• Annual wellness stipend, mental health resources, and access to virtual fitness classes.
• Generous parental leave and support for new parents.
• Continuous learning stipend and access to industry conferences.
• Monthly team lunches (virtual or in‑office) and quarterly company retreats.
• Access to a company‑wide mentorship program and leadership development tracks.

How to Apply

If you’re ready to lead the data transformation that powers brighthush’s customer experience, we’d love to hear from you. Submit your resume, a brief cover letter outlining your most impactful data engineering project, and any relevant portfolio or GitHub links.

Ready to make data‑driven decisions that shape millions of lives? Apply for this role now and join a team that turns insight into action.