Data Infrastructure Engineer

• Keep production data pipelines running across a cloud data warehouse and a real-time streaming platform, catching problems before they turn into outages


• Tune warehouse performance, manage access roles, and keep compute costs in check as usage grows


• Configure and maintain streaming infrastructure (topics, partitions, consumer groups) so data moves in near real time without gaps or duplicates


• Build automated checks that catch bad data, failed loads, or delivery delays before anyone downstream notices


• Write scripts and small tools in Python and SQL to cut down manual, repetitive pipeline work


• Support CI/CD for data infrastructure changes so updates ship safely and roll back cleanly if something breaks


• Work with data engineering and analytics teams to fix root causes, not just symptoms, when pipelines fail

What we're looking for

• Hands-on production experience running and tuning a cloud data warehouse (Snowflake or similar)


• Real, working experience with a streaming platform (Kafka or similar): producers, consumers, schema handling, and troubleshooting


• Comfortable in SQL and at least one scripting language, Python preferred


• Experience with a major cloud provider (AWS, Azure, or GCP)


• Familiarity with orchestration tools like Airflow or dbt


• Solid grasp of data modeling and the full data lifecycle, from ingestion to delivery


• Able to explain a pipeline issue clearly to both engineers and non-technical stakeholders