Data Engineer
Frida
| Company | Frida |
| Category | Engineering |
| Location | Miami |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 3 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (workable) |
Description
Who We Are Parenting isn’t picture-perfect. It’s messy, hilarious, exhausting, and life-changing — sometimes all before noon. That’s where we come in. Founded in 2014 by our CEO Chelsea Hirschhorn, Frida was built to make the raw reality of parenting a little easier to navigate (and a lot less overwhelming). It all started with one legendary snot-sucker — the NoseFrida — and has grown into a 200+ product lineup that supports families through every stage: from fertility and postpartum recovery to baby care and beyond. We don’t shy away from the stuff no one else wants to talk about — nipple pain, diaper blowouts, or the emotional rollercoaster that comes with keeping a tiny human alive. We call it like it is, solve the problems that actually matter, and build products that help parents feel seen, supported, and totally capable. You can now find Frida products in 50+ countries and thousands of stores across the U.S., from the biggest national retailers to your neighborhood grocery aisle. Under Hirschhorn’s leadership, Frida has become a category leader by challenging taboos, championing honesty, and supporting families at every stage of parenthood and beyond, earning acclaim on TIME's 100 Most Influential Companies, TIME Best Inventions, Fast Company Most Innovative Companies and Fast Company Brands That Matter. But the real win? Knowing we’re helping parents everywhere feel a little more human and a little less alone. How You Will Make an Impact Frida is seeking a Data Engineer to design, build, and maintain scalable data pipelines and the underlying database infrastructure that supports analytics and reporting across the organization. This role sits within the Data Integration and Architecture team and is central to our ongoing data lake buildout. This role will focus on ensuring database stability, proper indexation, reliable backups, performant pipelines, and sound data model and schema design. Strong collaboration with the analytics team will be essential to ensure they have a reliable, well-governed platform to build on. Responsibilities to include: Database Infrastructure & Reliability Build, optimize, and maintain data models and schemas within PostgreSQL, ensuring proper indexation, partitioning, and structural integrity to support downstream consumption. Own database backup, recovery, and disaster recovery procedures to ensure data durability and business continuity. Monitor database health, query performance, and resource utilization, proactively addressing issues before they impact downstream systems. Contribute to the architecture and continued buildout of the organization's data lake on Azure, including storage design, lifecycle policies, and environment reliability. Take ownership of deployment, security, and environment configuration from vendor teams, partnering with infrastructure and DevOps resources to bring these capabilities in-house. Data Pipelines & Integration Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory to ingest, transform, and load data from a variety of source systems. Implement and enforce data quality checks, monitoring, and alerting across pipelines. Troubleshoot pipeline failures and performance bottlenecks, performing root cause analysis and implementing lasting fixes. Governance & Collaboration Partner with business stakeholders and the analytics team to understand data ingestion requirements, ensuring data models and schemas are designed to meet current and future needs without duplicating tables or data across the environment. Drive standardization and templatization of data structures, pipeline patterns, and ingestion processes to ensure consistency, reduce technical debt, and make the platform easier to scale. Ensure the analytics team has access to clean, performant, and well-documented data by maintaining reliable data structures and pipeline outputs. Document data flows, lineage, and pi
991,236 openings. Erioun finds yours.Scored against your own profile, every hour.Try the radar →