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# Data Engineer

- **Company:** Tatari, Inc.
- **Location:** New York, United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Computer Programming, Extract Transform Load (ETL), Software Debugging, Distributed Data Store, Python (Programming Language), Online Analytical Processing, Performance Tuning, Raw Data, SQL Databases, Workflow Management Systems, Apache Spark, Backend, Data Lakes, Pyspark, Front End Software Development, Vertica, Data Pipelines, Databricks
- **Published:** July 28, 2026
- **Apply:** https://www.dice.com/job-detail/8d74363e-743f-46b2-8cb6-7390c8eea5e8

## About the Role

As a Senior Data Engineer in our Reporting and Measure pillar, you will design, build and own the large-scale data pipelines that turn high-volume raw data into curated, production-grade datasets powering Tatari's reporting and measurement products. You will be responsible for taking data products from requirements through tech spec, implementation, validation and production rollout-partnering closely with data science on methodology, backend and frontend engineers on serving layers, and product on requirements. The ideal candidate will have deep expertise in building and operating ETL pipelines at scale, a strong data quality and validation mindset, and a proven track record of owning datasets end-to-end in a cross-functional environment.
Your skills and experience:

 * 5+ years of dedicated experience designing, building and operating production ETL pipelines at scale
 * Strong programming skills in Python (or a similar language) and SQL; deep hands-on experience with Spark/PySpark. We use Databricks and Delta Lake here
 * Experience with workflow orchestration tools such as Airflow, including DAG design, backfills and failure recovery
 * Strong data modeling skills for analytics - curated/gold-layer datasets, schema design, partitioning and data contracts consumed by downstream services
 * Ongoing interest in agentic developer workflows: testing agent harnesses, building them, agent loop engineering, and similar emerging paradigms. You enjoy learning how they're reshaping the way software gets built.
 * A rigorous approach to data quality: validation, reconciliation and methodology comparison as part of shipping any dataset
 * Experience debugging distributed data systems - performance tuning, memory issues, and optimizations
 * Strong written communication and cross-functional collaboration skills, from tech specs to incident writeups
 * Bonus points if you have experience with OLAP stores (e.g., ClickHouse)



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