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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** INFINITE EDGE LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $175,000.0 - $240,000.0 - **Contract:** Permanent contract - **Skills:** Airflow, Information Engineering, Data Infrastructure, Data Systems, Data Warehousing, Software Debugging, Mobile Application Software, Raw Data, Standard Sql, Snowflake, Data Pipelines - **Published:** July 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d57788e66cb080c9 ## About the Role * 5+ years of experience in data engineering, analytics engineering, or a similarly demanding technical environment, ideally with startup or high-growth exposure. * A track record of building reliable data infrastructure and pipelines in ambiguous, fast-moving environments without needing a detailed playbook. * Strong SQL and pipeline/orchestration experience (e.g., dbt, Airflow, or similar), plus deep hands-on experience with Snowflake. * Experience with a modern ELT/ingestion tool (Airbyte, dlt, or similar) and a modern BI/visualization tool (Omni, Sigma, or similar). * Excellent written and verbal communication, with the ability to translate technical complexity into clear tradeoffs for non-technical stakeholders. * High ownership and strong follow-through, you're the person who makes sure the data is right and the pipeline doesn't break at 2am. * Low ego and strong relationship instincts. You influence through clarity, trust, and execution rather than title. * Strong engineering fundamentals and attention to detail, especially around data quality, testing, and observability. * Comfort operating in a fast-moving environment where priorities shift and the answer isn't always obvious. * Genuine curiosity about consumer brands, watches, marketplaces, paid growth, and how a high-growth company actually uses data to make decisions. * Willingness to do both strategic and unglamorous work, from architecting a data model to tracing down a broken event. Nice to Have * Experience at a high-growth startup or consumer company. * Experience with e-commerce, marketplaces, mobile app analytics, or mystery box / randomized-value product economics. * Familiarity with marketing and lifecycle tools like Braze, Apple Search Ads, Meta, or attribution platforms, and their data exports. * Experience building data infrastructure that supports finance, inventory, and paid acquisition reporting simultaneously. ## Description IcyBox is looking for a Senior Data Engineer to own the data infrastructure that powers a fast-moving, high-growth consumer business. This is a high-impact, execution-focused role for someone who thrives in ambiguity, moves fast, and knows how to build reliable, scalable data systems across a complex, fast-changing organization. You'll be the connective tissue between product, marketing, finance, and operations, owning the pipelines, models, and infrastructure that turn raw activity into the numbers everyone else relies on. You'll help build the data foundation that lets IcyBox scale from a fast-moving watch commerce and mystery box business into a durable consumer brand. This role is ideal for someone who is technically sharp, operationally strong, and energized by being close to the center of the business. You'll get exposure to strategic decisions, company-building problems, and cross-functional execution from day one, with the autonomy to identify what needs to happen and drive it forward yourself. This is not a purely back-end role. It's a builder/operator role for someone who can move from a data model to a pipeline outage to a stakeholder conversation about what a metric actually means without losing momentum. Some days you'll be building a new pipeline from scratch. Some days you'll be debugging why a dashboard number looks wrong at 11pm. Some days you'll be building a system that makes the whole company sharper every week after you're done. What You'll Do * Design, build, and maintain the data pipelines and infrastructure that power reporting, analytics, and product decisions across the company. * Own the Snowflake data warehouse architecture, including schema design, transformation logic, and data quality monitoring. * Partner directly with marketing, finance, and product to define key events, metrics, and attribution logic, including activation events like box_opened and downstream funnel tracking. * Build and maintain the systems that support real-time and batch reporting, from RTP and inventory economics to paid acquisition performance. * Serve as the connective tissue between raw data and the rest of the company, surfacing data quality issues early and keeping pipelines reliable. * Own integrations with third-party tools and platforms, including marketing, lifecycle, and attribution systems. * Build lightweight tooling, dashboards, and documentation that make self-serve analytics possible for non-technical stakeholders. * Investigate and resolve data discrepancies between systems, building processes and tests that reduce future error. * Own or support vendor and platform relationships tied to the data stack, including evaluation, negotiation, and renewals. * Step into urgent or high-priority data issues when the owner is unclear, and create a path to resolution. * Create documentation, models, and engineering playbooks that make repeatable work easier as IcyBox scales., IcyBox is moving quickly across product, marketing, operations, sourcing, fulfillment, and customer experience, and every one of those functions depends on data that's accurate, timely, and trusted. The Senior Data Engineer will help create the infrastructure and rigor that let the team make faster, better decisions without second-guessing the numbers. This person will be trusted with high-priority work, exposed to the full business, and expected to make IcyBox's data foundation stronger every single week. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [7 Most Popular Web Developer Jobs in Europe](https://www.wearedevelopers.com/magazine/163-7-most-popular-web-developer-jobs-in-europe)