Skills Required
The required candidate should have strong Python and SQL skills with hands-on experience in building and maintaining ETL/ELT data pipelines for operational metrics. The candidate should understand data warehouse concepts, data modeling, dbt framework, data quality checks, pipeline monitoring, and SQL query/cost optimization. Experience with data ingestion tools such as Debezium, Fivetran, Kafka/Kafka Connect, or similar is preferred. The candidate should have exposure to modern data warehouse or analytics platforms such as Snowflake, ClickHouse or similar. The candidate should also be able to build dashboards and visualizations using Grafana, Kibana, PowerBI, or similar tools to help SRE and platform teams troubleshoot system health, usage patterns, and performance bottlenecks.
Job Description
The customer is looking for a Data Engineer to design, build, and maintain data pipelines and data warehouse models for operational metrics. The role involves collecting data from servers, network devices, custom applications, and internal systems, then transforming, validating, and storing the data in a scalable data warehouse, lakehouse, or time-series data platform.
The candidate will work with SREs, Platform Engineers, and Product Owners to convert data requirements into reliable pipelines, optimized SQL/dbt models, and self-service dashboards. The role also includes data quality checks, pipeline monitoring, query and warehouse cost optimization, dashboard development, and troubleshooting pipeline or data accuracy issues.
