Mid-Level Data Engineer

hiro analytics • United State
Remote
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AI Summary

Hiro Analytics is seeking a mid-level Data Engineer to design, build, and maintain ETL pipelines, optimize databases, and architect systems for their marketing analytics platform.

Key Highlights
Design and maintain ETL pipelines
Optimize databases for performance at scale
Contribute to infrastructure architecture decisions
Key Responsibilities
Design, build, and maintain ETL pipelines
Optimize PostgreSQL and Snowflake databases for performance at scale
Build and maintain API integrations with e-commerce and marketing automation platforms
Contribute to infrastructure architecture decisions
Develop and maintain data models for marketing attribution, customer segmentation, cohort analysis, and lifetime value calculations
Monitor data quality, build validation checks, and troubleshoot pipeline failures
Technical Skills Required
PostgreSQL Python RDS S3 Athena Snowflake OAuth REST
Benefits & Perks
Salary range $105,000–$145,000
Fully remote
Nice to Have
Experience with multi-tenant SaaS data architectures
Familiarity with tools like Retool
Comfortable using AI coding tools (Claude Code, Copilot, etc.) to accelerate development

Job Description


Hiro Analytics is a marketing analytics platform built for agencies and brands. We integrate with platforms like Klaviyo, Sendlane, Attentive, Postscript, Omnisend, and Shopify to give marketing teams deeper visibility into what's actually driving revenue. We're a small, fast-moving team building infrastructure that processes e-commerce data at scale.


About the Role

We're looking for a mid-level Data Engineer to own and evolve the data infrastructure that powers our analytics platform. You'll work across the full data stack — designing ETL pipelines, optimizing analytics databases, and architecting the systems that ingest data from marketing and e-commerce platforms. This is a high-impact role where your decisions directly shape how agencies and brands understand their customers.


What You’ll Do

  • Design, build, and maintain ETL pipelines that move data from marketing platforms (Klaviyo, Attentive, Shopify, etc.) into our analytics layer
  • Optimize PostgreSQL and Snowflake databases for performance at scale — indexing strategies, query optimization, materialized views
  • Build and maintain API integrations with e-commerce and marketing automation platforms, including handling OAuth flows, pagination, and rate limiting
  • Contribute to infrastructure architecture decisions — evaluate and improve how we use current technologies (Aurora, S3, Athena, Snowflake) to support growing data volumes and new analytics workloads
  • Develop and maintain data models for marketing attribution, customer segmentation, cohort analysis, and lifetime value calculations
  • Monitor data quality, build validation checks, and troubleshoot pipeline failures


What We’re Looking For

  • High ownership, high urgency — you default to action, take initiative, and drive work to completion without heavy oversight.
  • 3+ years of experience in data engineering or a closely related role
  • Strong PostgreSQL skills — you're comfortable writing complex queries, designing schemas, and tuning performance 
  • Proficient in Python for building and maintaining ETL pipelines, with a strong sense of tradeoffs between compute, storage, and speed
  • Hands-on experience with RDS, S3, Athena, Snowflake or similar managed services
  • Experience building and maintaining integrations with third-party APIs (REST, OAuth)
  • Familiarity with e-commerce data models and/or marketing analytics data (a meaningful plus)
  • Ability to reason about infrastructure tradeoffs and propose architectural improvements independently


Nice to Have

  • Experience with multi-tenant SaaS data architectures
  • Familiarity with tools like Retool
  • Comfortable using AI coding tools (Claude Code, Copilot, etc.) to accelerate development
  • Exposure to marketing platforms like Klaviyo, Shopify, Meta, GA


Compensation & Benefits

  • Salary range $105,000–$145,000 depending on experience
  • Fully remote



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