Senior Data Engineer: Scale ETL & Analytics Pipelines

Tatari Inc; New York (NY); Hybrid; USD 170,000 - 200,000; Full time

Benefits offered by this job

Health insurance

Equity compensation

401K

FSA

Commuter benefits

Monthly spending account

Education benefit

Newbie Productivity Perk

Unlimited PTO

Wellness day off

Snacks and catered lunches

Team building events

Hybrid RTO (2 days in office)

Job summary

Tatari Inc. is seeking a Senior Data Engineer to design, build and own large-scale ETL pipelines powering our reporting and measurement products.

You will work closely with data science, backend and frontend engineers, translating requirements into production datasets with a strong focus on data quality and validation. The role emphasizes end-to-end ownership of datasets, plus opportunities to explore agentic developer workflows and cross-functional collaboration in a hybrid environment.

Qualifications

• 5+ years designing, building and operating production ETL pipelines at scale.
• Strong programming in Python and SQL with Spark/PySpark.
• Experience with Airflow, DAG design, backfills and failure recovery.
• Data modeling for analytics with curated datasets and contracts.
• Interest in emerging agentic developer workflows and data quality.
• Ability to diagnose distributed data systems and optimize performance.

Responsibilities

• Design, build and own large-scale data pipelines for Tatari's reporting and measurement.
• Collaborate with data science, backend/frontend engineering and product on requirements.
• Ensure data quality, validation and end-to-end dataset ownership.

Skills

ETL pipelines

Python

SQL

Spark/PySpark

Airflow

Databricks

Delta Lake

Data modeling

Cross-functional collaboration

Data quality

Tools

Databricks

Delta Lake

Airflow

Job description

Tatari Inc. is seeking a Senior Data Engineer to design, build and own large-scale ETL pipelines powering our reporting and measurement products.

You will work closely with data science, backend and frontend engineers, translating requirements into production datasets with a strong focus on data quality and validation. The role emphasizes end-to-end ownership of datasets, plus opportunities to explore agentic developer workflows and cross-functional collaboration in a hybrid environment.