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ETL Engineer
Job in
New York, New York County, New York, 10261, USA
Listed on 2026-05-16
Listing for:
MedReview Inc.
Full Time
position Listed on 2026-05-16
Job specializations:
-
IT/Tech
Data Engineer, Data Analyst, Data Science Manager, Big Data
Job Description & How to Apply Below
Position Summary
Med Review 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 Click House, 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- Design and develop ETL pipelines using SSIS, Azure Data Factory, and Databricks
- Build and optimize Click House ingestion pipelines (batch + streaming)
- Develop transformations for structured and semi-structured data
- Optimize SQL Server and Click House queries for performance and scalability
- Improve data models, partitions, and materialized views in Click House
- 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)
- ETL tools:
Azure Data Factory, SSIS, Databricks - Strong SQL skills (writing, optimizing, and troubleshooting complex queries)
- Experience working with Click House (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 + Click House exposure, you will not be a fit.
Nice to Have- Experience with streaming data (Kafka, Event Hubs)
- Exposure to big data frameworks
- Understanding of Dev Ops/Data pipeline deployment practices
- Experience supporting BI tools (Power BI, Tableau)
- 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
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