ETL Engineer

MedReview is looking for a hands-on ETL Engineer who knows how to build, optimize, and scale data pipelines in a high-performance environment. This is not an entry-level role. You will be working with modern data tools and large datasets, with a strong focus on ClickHouse, SQL performance, and real time data processing.

If you're someone who can take ownership of data pipeline end-to-end and thrives in a fast-paced data-driven environment, this role is for you.

This is an on-site role Monday - Thursday with remote Fridays. Candidates must be able to consistently work on-site. No exceptions. Salary $120-130K

Responsibilities

• You will be responsible for building and maintaining scalable ETL pipelines that power analytics and business intelligence.
• Design and develop ETL pipelines using SSIS, Azure Data Factory, and Databricks
• Build and optimize ClickHouse ingestion pipelines (batch + streaming)
• Develop transformations for structured and semi-structured data
• Optimize SQL Server and ClickHouse queries for performance and scalability
• Improve data models, partitions, and materialized views in ClickHouse
• Integrate data from multiple sources (APIs, SQL Server, cloud storage, Kafka/Event Hubs)
• Monitor pipeline performance and ensure low latency + high reliability
• Implement data quality checks, error handling and lineage tracking
• Partner with BI teams to support dashboards (Power BI, etc)

Must-Haves (Non-Negotiables)

We are targeting candidates who already have strong, hands-on experience in the following

• ETL tools: Azure Data Factory, SSIS, Databricks
• Strong SQL skills (writing, optimizing, and troubleshooting complex queries)
• Experience working with ClickHouse (schema design, ingestion, optimization)
• Experience with cloud environments (Azure perferred)
• Programing in Python or Scala for data processing
• If you do not have ETL + SQL + ClickHouse exposure, you will not be a fit.

Nice to Have

• Experience with streaming data (Kafka, Event Hubs)
• Exposure to big data frameworks
• Understanding of DevOps/Data pipeline deployment practices
• Experience supporting BI tools (Power BI, Tableau)

What Success Looks Like

• You can independently build and optimize ETL pipelines
• You understand how to make data systems faster, cleaner, and scalable
• You're comfortable working across engineering, analytics, and business teams
• You proactively identify performance issues and fix them