Lead Data Engineer

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BÆRSkin Tactical Supply Co. (divbrands)

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

🏭 Manufacturing

💼 Consulting

📦 Logistics

Manufacturing • Consulting • Logistics

BÆRSkin Tactical Supply Co. (divbrands) is a direct-to-consumer outdoor and tactical apparel brand that designs, manufactures and sells weatherproof hoodies, jackets, pants, backpacks and accessories for urban and outdoor use. The company emphasizes durable, technical materials and functional features (waterproofing, wind protection, modular/tactical styling) and positions its products for hikers, campers, outdoor workers and everyday city use. BÆRSkin operates an online store with retail and wholesale channels, promotes strong customer reviews and seasonal sales, and highlights gifting, bundles and gear tested by experts.

📋 Description

• Own the data platform architecture end to end, from ingestion through storage, transformation, modelling, and serving • Make architectural decisions about what to build, buy, and deprecate • Run the platform day to day, including pipeline tuning, cost management, data quality, observability, and incident response • Manage platform costs and evaluate managed versus self-hosted solutions using quantitative analysis • Partner with marketing, finance, and operations on attribution, cohorts, LTV, conversion, returns, and fulfilment margins • Translate commercial questions into models and datasets and reject low-value requests • Set modelling, review, testing, and AI-use patterns for the data team • Pair with and mentor the other data engineer through hands-on delivery • Build documented models, coherent semantics, and trusted self-service dashboards • Reduce ad-hoc data requests and enable business self-service • Remove the CTO as the bottleneck for data architecture decisions • Improve platform reliability and self-serviceability within the first 90 days

🎯 Requirements

• At least 7 years of hands-on experience in data engineering, data architecture, or analytics engineering • Experience owning a data platform end to end • Advanced Python and SQL, including window functions, CTEs, query plans, and partitioning • Experience designing and running a production data platform and making durable architectural decisions • Strong modelling judgment across warehouse, lake, and lakehouse architectures • Production experience with orchestration such as Airflow, Dagster, or Prefect • Production experience with transformation tools such as dbt or equivalent • Experience with a cloud analytical warehouse at scale; BigQuery preferred, with Snowflake, Redshift, or ClickHouse accepted • Experience owning a platform budget and reducing costs without breaking the platform • Daily AI-augmented development workflow, with specific before-and-after examples • Commercial acumen connecting platform decisions to revenue, cost, or customer impact • English at B2/C1 minimum • Four hours of overlap with EU working hours • Hands-on builder able to execute independently • Pragmatic, direct, collaborative, and coachable working style • Portuguese is desirable • Consumer-facing, high-volume commercial domain experience is desirable • Databricks and distributed processing experience is desirable • Streaming and near-real-time experience is desirable • Terraform, Docker, CI/CD for data workflows, and platform reliability practice are desirable • T-shaped or pi-shaped technical background is desirable • Founder experience is a plus • Mentoring experience without formal management is desirable

🏖️ Benefits

• Fully remote • Competitive salary with regular performance reviews • 26 days paid leave • Parental leave • Training and budget towards professional-level cloud certification • Architectural authority from day one, with a CTO who wants to hand it over • A stack you can change • AI tools may be used during technical stages and on the job