Data Engineer

This is a remote position.

• 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 the 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.
  

Desirable Qualifications

• 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.