[Hiring] Data Engineer @Sandboxx

Data Engineer

About Sandboxx

Sandboxx is the industry-leading platform connecting military recruits with their support system through physical mail, in-app messaging, and a rapidly growing online community. Every week, tens of thousands of recruits send letters that forge unbreakable bonds with family and friends—and drive thousands of new users into our ecosystem.

About the Role

You love digging into data and making it sing—and at Sandboxx, you’ll be the person everyone leans on when they need answers. You’ll sit at the intersection of engineering and business—partnering closely with Marketing, Product, and our Executive team—to build trusted pipelines, analytics models, and dashboards that power everything from day-to-day operations to board-level reporting.

This is a hands-on role. You’ll build and maintain ELT workflows, plug in third-party APIs (CDPs, MMPs, Iterable, partner feeds, etc.), and scale our BI stack with BigQuery, Airflow, and Looker (or Looker Studio). 

Sandboxx’s growth and operations run on data, and your work will turn messy, complex feeds into clean, trusted insights—so nobody ever has to wait in a queue for the story behind the numbers.

Why We’re Hiring For This Role Now

• Our data lives in pockets of well-built pipelines—but without integration, we lack a holistic view of our customer journey.
• Teams wrestle with one-off queries and spreadsheets to get the needed numbersjust to get the numbers they need, blocking deeper analysis.
• We don’t have a unified attribution model or single source of truth, so it’s hard to tie marketing and product efforts back to real impact.
• Real-time insights are out of reach, forcing stakeholders into reactive mode instead of proactive optimization.
• There’s no dedicated owner of our BI layer—no one ensuring data consistency, reliability, and accessibility across the company.

What You’ll Be Responsible For

• Designing, building, and maintaining robust ELT workflows that consolidate data from all internal and external systems into our warehouse
• Integrating with third-party platforms—Iterable, mParticle, partner APIs, and more—to ensure every metric is consistently captured
• Architecting and optimizing our BigQuery environment for performance, cost-efficiency, and scalability
• Modeling data and authoring Looker (Looker Studio, Tableau, etc.) dashboards that give every team self-serve access to reliable insights
• Implementing automated tests and monitoring to catch data issues early and maintain trust in our metrics
• Writing clear documentation and hosting regular “office hours” to empower non-technical teammates to explore data confidently
• Collaborating with BI analysts to establish standards, conduct code reviews, and foster company-wide data ownership
• Owning and maintaining ELT pipelines using Apache Airflow, custom scripting, and BigQuery
• Contributing to data governance, access controls, and system scalability as our platform grows

What We’re Looking For

• A hands-on data engineer who loves turning ambiguity into clarity and takes pride in seeing teams succeed with the metrics you build
• Deep experience designing and maintaining ELT pipelines in a cloud warehouse (BigQuery, Snowflake, or Redshift) using orchestrators like Airflow or Prefect
• SQL mastery—you can write, optimize, and troubleshoot complex queries without hesitation
• Proven track record with dbt (or an equivalent) for modular, testable transformations and a CI/CD mindset for data workflows
• Comfort modeling data and building self-serve dashboards in Looker, Tableau, or Power BI that non-technical teammates lean on daily
• A relentless focus on data quality—automated tests, monitoring, and clear documentation are second nature to you
• Excellent communicator who can translate technical details into actionable insights for Marketing, Product, Finance, and leadership
• A builder’s mentality: you see gaps in our analytics stack and jump in to solve them rather than waiting for direction

What Success Looks Like

Within the first month, you’ll

• Deliver a “data health” report that maps existing sources and prioritizes the top three manual processes for automation
• Ship your first ELT job into BigQuery and launch a simple dashboard tracking a key operational metric

Within the first 3 months, you’ll

• Roll out a core dashboard showing acquisition, activation, retention, and LTV—auto-refreshing daily with anomaly alerts
• Migrate our transformation logic into a CI/CD pipeline with a suite of tests that prevent bad data from reaching analysts

Within the first 6 months, you’ll

• Automate the monthly finance close report—P&L, CAC analysis, cohort performance—in under 24 hours after month-end
• Launch a self-serve data sandbox in Looker where non-engineers can safely explore and query cleaned data

After 12 months, you’ll

• Centralize all key data sources into a well-documented, reliable warehouse with minimal pipeline failures
• Enable 80% of dashboards to be built and maintained by analysts and power users using your data models
• Cut average query times by at least 50% through schema tuning, caching strategies, and optimized transformations

What You’re Like

• Using Airflow, Prefect, or similar, you’ve built production ELT pipelines in a cloud data warehouse (BigQuery, Snowflake, or Redshift).
• SQL is second nature—you write complex transformations, optimize performance, and debug slow queries with confidence
• Hands-on experience with dbt (or an equivalent) and a track record of shipping modular, tested data models
• You’ve authored dashboards in Looker, Tableau, or Power BI that non-technical teams rely on daily.
• You care deeply about data quality—writing tests, documenting pipelines, and monitoring health so trust in “the numbers” never wavers.
• You communicate clearly, whether you’re walking a marketer through a dashboard or presenting metrics to the Executive team.

Ideally, you

• Have a bachelor’s degree in a technical field such as Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related discipline
• Have scaled a data stack from thousands to millions of daily events, maintaining pipeline reliability under heavy load
• Built analytics models for subscription-driven businesses, mastering cohort, funnel, and revenue attribution analyses
• Integrated multiple marketing and engagement platforms (Iterable, Segment, Branch, Adjust) so acquisition metrics flow seamlessly into your warehouse
• Enjoy mentoring—running data office hours, pairing on complex queries, and helping teammates level up their SQL skills
• Have experience with reverse-ETL or operationalizing insights to feed marketing and product tools directly

Bonus Points For

• Prior work with military, veteran, or family‑support organizations
• Startup or high‑growth environment exposure
• Experience with dbt or custom transformation frameworks
• Familiarity with marketing and product analytics stacks

Compensation, Benefits & Perks

• Equity incentive plan
• 401k with matching and sharing
• Top-tier health insurance and family benefits
• Flexible paid vacation
• Paid parental leave

We look for people with a good sense of humor and zest for life, especially during interviews.

Sandboxx is an equal opportunity workplace and we would like to hear from all qualified applicants. If you have a disability or any special needs that we might need to accommodate, please just let us know.