Data Engineer

Job not on LinkedIn

🕒 Yesterday

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 24%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Rayda

WebsiteLinkedInAll Job Openings

11 - 50 employees

📦 Logistics

💼 Consulting

🏥 Healthcare

💰 Pre seed on 2023-02

Logistics • Consulting • Healthcare

Rayda is a SaaS platform that automates global employee device lifecycle management for companies. It handles procurement, pre-configuration, international shipping, tracking, maintenance, secure data wiping, retrieval, storage, insurance, and sustainable disposal across 170+ countries, enabling IT, HR, and operations teams to equip remote employees quickly and reliably. Rayda centralizes device tracking and documentation, reduces device-related tickets and costs, and accelerates onboarding and offboarding workflows for distributed, enterprise customers.

📋 Description

• Design, build, deploy and maintain scalable, production-grade data pipelines and ETL/ELT workflows. • Integrate data from operational databases, APIs, CRM systems, product analytics, IT ticketing platforms and device telemetry. • Evaluate and implement appropriate data warehouses, lakehouses and analytical databases. • Develop reliable data models and reusable datasets for business reporting, product analytics and customer-facing applications. • Build data infrastructure supporting customer intelligence dashboards, anomaly detection, predictive insights and AI-powered recommendations. • Establish data quality standards, automated validation, monitoring, alerting and recovery mechanisms. • Improve data collection, instrumentation, schema management and data documentation. • Implement secure data processing practices, access controls and customer-level data isolation. • Optimise data storage, processing performance, scalability and infrastructure costs. • Collaborate with Product, Engineering, Finance and Operations to translate business requirements into reliable data solutions. • Maintain technical documentation covering data architecture, integrations, pipeline dependencies and operational procedures.

🎯 Requirements

• Demonstrated experience designing, deploying and maintaining production-grade data pipelines. • Strong SQL proficiency and experience working with relational databases and complex datasets. • Hands-on experience with ETL/ELT processes, incremental data processing, transformations and pipeline monitoring. • Proficiency in Python or another suitable data engineering programming language. • Experience integrating databases, REST APIs, SaaS platforms and external data sources. • Experience designing and implementing data warehouses, lakehouses or analytical data platforms. • Strong knowledge of data modelling, data quality, validation and schema management. • Familiarity with cloud infrastructure, data storage, access controls and production reliability. • Ability to evaluate technical architecture based on performance, scalability, cost and business requirements. • Strong analytical, problem-solving and independent execution skills. • Experience working with B2B SaaS platforms and multi-tenant architectures. • Familiarity with dbt, Airflow, Dagster, ClickHouse, BigQuery or Snowflake. • Experience with device telemetry, time-series data, IT operations or cybersecurity platforms. • Knowledge of event-driven architecture, streaming data and high-volume operational events. • Experience building data infrastructure for AI, machine learning or predictive analytics. • Previous experience in an early-stage or high-growth technology environment.

🏖️ Benefits

• Opportunity to build foundational data infrastructure supporting a growing global IT operations platform. • Ownership of important engineering architecture and technical decisions. • Opportunity to develop data solutions that directly influence customer-facing product capabilities. • Exposure to data engineering, AI-powered intelligence and emerging IT operations technologies. • Cross-functional collaboration with Product, Engineering, Finance and Operations. • Opportunity to solve complex, real-world data challenges and contribute to Rayda's product evolution.