Senior Data Engineer

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Darkroom

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤝 B2B

☁️ SaaS

Marketing • B2B • SaaS

Darkroom is a world-class growth marketing company specializing in services that span the entire customer journey. As the 385th fastest growing private company in America according to the Inc. 5000 in 2023, Darkroom focuses on maximizing ROI for its clients. They offer services such as Amazon Marketplace Management, Creative Services, Paid Media Management, Retention Marketing, and Website Optimization. With a strong emphasis on integrating finance, creativity, and performance into growth marketing strategies, Darkroom leverages data infrastructure and attribution to enhance advertising effectiveness and profitability. Their committed approach has created over $1 billion in attributable revenue for clients, making them a trusted partner for leading companies worldwide.

📋 Description

• Build and scale the ingestion layer across third-party marketing APIs (Meta, Google, TikTok, GA4, Shopify, Klaviyo, and more) — auth, extraction, rate-limit handling, backfill, and incremental sync. • Design normalization and transformation pipelines that map messy, platform-specific data into shared, queryable schemas (e.g. a unified creative/campaign/order model). • Own data reliability at scale — sync accuracy, freshness, coverage, and observability. Build the systems that detect when a connection breaks or a number looks wrong before a user does. • Engineer for multi-tenant scale and security: pipelines and storage that stay performant and cost-efficient across 1,000+ users and hundreds of connected brands — with strict data isolation, privacy, and compliance built in, not bolted on. • Partner with the AI and data-science teams to expose clean, well-modeled data the agent can retrieve and reason over.

🎯 Requirements

• Experience building and operating large enterprise data pipelines engineered for scale — systems serving 1,000+ users (or equivalent data volume / tenancy), where reliability, isolation, and cost at scale were real constraints you solved. • Strong SQL and Python, with production experience in a modern data warehouse (BigQuery, Snowflake, Redshift, or similar). • Deep familiarity with ETL/ELT patterns, incremental sync, schema design, and data modeling for analytics. • Built and maintained integrations against third-party APIs — OAuth flows, pagination, rate limits, schema drift, and the operational reality of connectors that break. • A bias toward observability and data quality: you instrument your pipelines and you don't ship data you can't trust. • Experience building or operating within SOC 2-compliant systems with enterprise-grade security and privacy — you've handled sensitive customer data under real compliance constraints (access controls, encryption, data isolation, auditability) and treat it as a first-class engineering requirement.

🏖️ Benefits

• Product Ownership: You'll ship production code daily and help steer key product and technical decisions. • Shape the Engineering Culture: You'll influence how we work—tools, processes, standards, and hiring. • Work with Challenger Consumer Brands: Talk directly to customers (CEOs, CMOs, VP's) of fast-growing consumer brands—some doing $80M–$500M in revenue.