Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, deploy, and maintain scalable, production-quality data pipelines and ETL/ELT workflows.

• Integrate data from various sources including operational databases, APIs, CRM systems, product analytics, IT ticketing systems, and device telemetry.

• Assess and implement suitable data warehouses, lakehouses, and analytical databases.

• Create dependable data models and reusable datasets for business reporting, product analytics, and customer-facing applications.

• Develop data infrastructure that supports customer intelligence dashboards, anomaly detection, predictive insights, and AI-driven recommendations.

• Set data quality standards along with automated validation, monitoring, alerting, and recovery mechanisms.

• Enhance data collection, instrumentation, schema management, and documentation practices.

• Enforce secure data processing protocols, access controls, and customer-level data segregation.

• Optimize data storage, processing efficiency, scalability, and infrastructure expenses.

• Collaborate with Product, Engineering, Finance, and Operations teams to translate business needs into reliable data solutions.

• Maintain technical documentation that outlines data architecture, integrations, pipeline dependencies, and operational procedures.

⛳️ Requirements

• Proven experience in designing, deploying, and maintaining production-grade data pipelines.

• Strong proficiency in SQL and experience working with relational databases and complex datasets.

• Practical experience with ETL/ELT processes, incremental data processing, transformations, and pipeline monitoring.

• Proficient in Python or another relevant data engineering programming language.

• Experience in integrating databases, REST APIs, SaaS platforms, and external data sources.

• Background in designing and implementing data warehouses, lakehouses, or analytical data platforms.

• Strong understanding of data modeling, data quality, validation, and schema management.

• Familiarity with cloud infrastructure, data storage solutions, access controls, and production reliability.

• Ability to assess technical architecture based on performance, scalability, cost, and business needs.

• Strong analytical, problem-solving skills, and the ability to work independently.

• Experience with B2B SaaS platforms and multi-tenant architectures.

• Familiarity with tools such as 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 in building data infrastructure for AI, machine learning, or predictive analytics.

• Prior experience in an early-stage or high-growth technology setting.

🏝️ Benefits

• Opportunity to construct foundational data infrastructure that supports a rapidly growing global IT operations platform.

• Ownership of significant engineering architecture and technical decisions.

• Chance to develop data solutions that have a direct impact on customer-facing product features.

• Exposure to data engineering, AI-driven intelligence, and emerging technologies in IT operations.

• Opportunities for cross-functional collaboration with teams in Product, Engineering, Finance, and Operations.

• Ability to tackle complex, real-world data challenges and contribute to Rayda's product development.