Senior Data Engineer, Data Platform

United States


Tatari combines TV advertising with real-time data to ensure your TV Ads are optimally managed. Contact us today.

View company page

Tatari is on a mission to revolutionize TV advertising. We work with some of your favorite disruptor brands—like Calm, Fiverr, and OneWheel—to grow their business through linear and streaming TV. We combine a sophisticated media buying platform with proprietary analytics to turn TV advertising into an automated, digital-like experience.


Named one of the Hottest Ad Tech Companies by Business Insider, and Best Places to Work by Inc. Magazine for the third consecutive year, our team includes founders and leaders from Google, Microsoft, Stripe, Shazam and Facebook. We are growing rapidly as we accelerate our mission to automate the complex landscape of managing and measuring television advertising. We have a long-term goal to make marketing on TV available to businesses of any size.

As a data and analytics adtech company, Tatari relies on a wide, heterogeneous and ever evolving set of data sources, upon which our data scientists build predictive models for television buying and analytics and our clients make critical spend decisions to maximize advertising spend ROI. 

As a data engineer on the Data Platform team, you will help level up Tatari’s data platform by designing, building and scaling the infrastructure which powers all of our data engineering, data science and analytics efforts. You will be responsible for laying down industry standard data engineering practices and solutions, bringing in new technologies when necessary and doubling down efforts to scale current data infrastructure. The ideal candidate will have strong infrastructure and data engineering skills, a proven track record of successfully building and scaling data infrastructure leveraged by growing companies as well as the ability to evangelize and drive new infrastructure adoption.

Your skills and experience:

  • 5+ years of dedicated data engineering experience building data pipelines, and maintaining and scaling data infrastructure
  • 5+ years of experience working with cloud based infrastructure. We use AWS here. 
  • Strong programming skills in Python or a similar language
  • Strong experience deploying and managing open source frameworks such as Airflow, Kafka, Spark, Kubernetes, etc.
  • Comfortable working with SQL, Spark/PySpark, and Data Lakehouses
  • Strong experience scaling and managing on-premise and cloud based database deployments
  • Experience with security, controls and access management for data


  • Competitive salary ($170,000 to $210,000 annually)
  • Equity compensation
  • 100% health insurance premium coverage for you and your dependents
  • Unlimited PTO and sick days
  • Snacks, drinks, and catered lunches at the office
  • Team building events 
  • $1000 annual continued education benefit
  • $500 WFH reimbursement
  • $125 pre-tax monthly stipend to spend on whatever you want
  • Annual mental health awareness app reimbursement
  • FSA and commuter benefits
  • Monthly Company Wellness Day Off (During WFH)

At Tatari, we believe in the importance of cultivating teams with diverse backgrounds and offering equal opportunities to all. We strive to create a welcoming, inclusive environment where every team member feels valued and diversity is celebrated.


Tags: Airflow AWS Data pipelines Engineering Kafka Kubernetes Open Source Pipelines PySpark Python Security Spark SQL Streaming

Perks/benefits: Career development Competitive pay Equity Gear Health care Home office stipend Team events Unlimited paid time off Wellness

Regions: Remote/Anywhere North America
Country: United States
Job stats:  10  1  0
Category: Engineering Jobs
  • Share this job via
  • or

More jobs like this

Explore more AI/ML/Data Science career opportunities

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.