Data Engineer

• 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.

• 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.

• 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.

Originally posted on Himalayas