Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Senior Data Analyst (BigQuery): Health & Wellness (3-month project)
- Remote from
- Brazil
- Salary
- Undisclosed
- Department
- Data Science & Analytics
- Employment
- Full Time
- Experience
- Director
- Published
- Apply before
- 8 Dec 2026
- Listing views
- 15
- Application actions
- 0
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About this role.
About Truelogic
At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.
Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.
By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.
Our Client
Our client is a well-known US-based fitness and wellness company that has built a strong consumer brand around premium, instructor-led fitness experiences. They combine a large physical studio presence with digital products that support class booking, memberships, and connected fitness experiences.
Job Summary
We are seeking a Senior Data Analyst / Data Manager to bridge the gap between technical data infrastructure and strategic business decision-making. You will build scalable data models in Looker/LookML and write advanced SQL in Google BigQuery to surface executive-level insights, trends, and growth opportunities across all business units.
Project Duration: 3 months, with possibility of renewal
Responsibilities
Insights & Recommendations: Partner with cross-functional teams and senior stakeholders to understand business questions, deliver timely analysis, and surface opportunities for data-driven improvement.
Visualizations & Dashboarding: Design and maintain ad-hoc and recurring Looker reports; build and monitor key business metrics; proactively identify trends and
performance gaps.
Data Modeling: Build, optimize, and document LookML models that support scalable, efficient analysis across the organization.
Infrastructure & Data Quality: Audit existing dashboards and data sources to identify consolidation opportunities; diagnose and resolve data discrepancies; partner with the Data Engineering team to improve data pipelines and ensure reporting accuracy.
Predictive Modeling: Develop and maintain models that forecast business outcomes, customer behavior, and other key metrics.
Subject Matter Expertise: Develop deep familiarity with the client’s full data landscape and contribute to evolving how the business measures performance.
Qualifications and Job Requirements
Must have
Experience: 4+ years of experience in data analytics, business intelligence, or data engineering.
SQL & Data Warehousing: Advanced SQL proficiency with hands-on expertise in Google BigQuery (query optimization, schema design, GCP).
BI & Modeling: Strong experience with Looker and LookML for data modeling, dashboarding, and report automation.
Preferred Tools: Python (pandas, matplotlib), Tableau, Jupyter Notebooks, AWS.
Domain Skills: Predictive modeling (regression, forecasting), metrics design, cross-functional stakeholder communication.
Nice to Have
Fitness Industry Experience: Prior experience in consumer tech, fitness, subscription-based businesses, or retail/hospitality.
Advanced Analytics & AI Tools: Exposure to predictive modeling (regression, customer churn/forecasting), Python (pandas, matplotlib), or AI-driven analytics workflows.
Additional BI Platforms: Familiarity with alternative visualization tools like Tableau or Jupyter Notebooks alongside Looker.
What We Offer
100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection.
Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings.
Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed.
Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock.
Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies.
Why You’ll Like Working Here
A Culture That Values You: We prioritize well-being and work-life balance, offering engagement activities and fostering dynamic teams to ensure you thrive both personally and professionally.
Diverse, Global Network: Connect with over 600 professionals in 25+ countries, expand your network, and collaborate with a multicultural team from Latin America.
Team Up with Skilled Professionals: Join forces with senior talent. All of our team members are seasoned experts, ensuring you’re working with the best in your field.
Apply now!
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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Sample interview questions
I first review the execution plan and bytes scanned, then reduce unnecessary columns and partitions, filter as early as possible, and use clustered or partitioned tables where appropriate. For recurring transformations, I also consider materialized views or scheduled aggregated tables to improve dashboard performance and cost efficiency.
I would begin by defining certified dimensions and measures in reusable views, then create governed explores with clear join relationships and access controls. I would document metric definitions, test joins for fanout issues, and use derived tables only where they provide a meaningful performance or modeling benefit.
I would validate the business definition first, then trace the metric through the LookML logic, SQL query, transformation layers, and source records. I would isolate differences in filters, time zones, grain, joins, late-arriving data, and refresh timing, document the root cause, and work with Data Engineering on a durable correction.
I would define churn precisely, establish a prediction window, and create features from membership tenure, attendance, booking behavior, purchase history, engagement, and payment events. I would evaluate a baseline model alongside interpretable approaches such as logistic regression, validate performance on holdout periods, and translate results into actionable retention segments.
I focus on the decision required, lead with the most important insight and business impact, and use concise visuals with clearly defined metrics. I explain assumptions and uncertainty in plain language, recommend specific next actions, and provide drill-down detail only when it supports follow-up questions.
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