Role Overview
Tatari is hiring a Staff Data Platform Engineer. This is a full-time role in San Francisco, California. Part of Tatari's Data Science hiring, posted 6 days ago. The posted range is $190k to $240k. Full responsibilities, required qualifications, and the apply link are listed in the description below.
Salary Context
This role offers $190k-$240k. The median for Staff-level Data Science roles is $203k-$260k (based on 28 listings). 7% below median.
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Job description
Tatari is on a mission to revolutionize TV advertising. Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent application of AI and machine learning, Tatari helps some of the world’s fastest growing brands including Chime, Calm, Tecovas, Manscaped, Saatva, and Liquid I.V., reach their customers using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience, enabling businesses of any size to advertise on TV.
That approach has earned Tatari broad industry recognition, including being named Best CTV AdTech Platform in the 8th annual MarTech Breakthrough Awards, as well as honors from Digiday (Best Connected TV Platform), AdExchanger (Most Innovative TV Advertising Technology), and Business Insider (Hottest AdTech Companies). Tatari has also been recognized as the Best Place to Work by Inc. Magazine. Backed by an executive team of former founders and senior leaders from companies including Shazam, TrueCar, AdapTV, LiveRail, Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising enters its next major era.
This is a systems and infrastructure position first. As a Data Platform Engineer, you will be responsible for the reliability, stability, and operational health of our data platform — including how it is deployed, monitored, maintained, and promoted across environments. Data engineering skills are a plus and will be developed on the job; what we cannot teach is operational discipline.
If you have spent your career keeping production systems alive, know what it feels like to break prod and never want to do it again, and treat lower environments as non-negotiable gates rather than suggestions — we want to talk to you.
This is not a data engineering role. You will not spend most of your time writing jobs or consuming the platform. You will be administering, scaling, hardening, and evolving it.
Responsibilities
- Own the reliability and availability of our data platform infrastructure across all environments
- Enforce and improve environment promotion discipline — staging is not prod, and prod is sacred
- Define and uphold SOPs around deployments, maintenance windows, and change management
- Instrument and monitor platform health using observability tooling; build alerting that means something
- Participate in architecture and deployment discussions; push back when something isn't ready
- Collaborate with data scientists, engineers, and product managers on infrastructure needs — as a partner, not an order-taker
- Identify and remediate reliability risks before they become incidents
- Support customer-facing and internal systems with a bias toward stability over velocity
Qualifications
The right candidate leans SRE. Data platform experience is additive — we will train the right person. Bullets marked with * are strongly preferred; all others are meaningful signal.
- Operational instinct — "the fear" — you've been burned by prod, you respect it, and you've built habits around it. You know what a proper maintenance window looks like, you communicate before you touch production, and you don't spin up new initiatives while something critical is still burning in.
- 3+ years in cloud infrastructure, SRE, or platform engineering (AWS preferred; GCP/Azure experience translates)
- High Availability architecture: blue/green deployments, data replication, load balancing
- Experience with workflow orchestration (Airflow or similar DAG-based schedulers — or general job scheduling/cron systems at scale)
- Strong Linux fundamentals and scripting (Bash, Python, or similar)
- Distributed data processing (Spark, PySpark, or similar big data frameworks — or experience managing clusters that run them)
- Containerization and orchestration (Kubernetes, Docker, or similar)
- Data ingestion, ETL, or streaming systems (Kafka, Flink, or similar — or experience operating message queues and pipelines)
- Infrastructure-as-code and provisioning (Terraform, Helm, or similar)
- OLAP and OLTP databases (Clickhouse, Postgres, Redshift, or similar — query patterns, indexing, and operational care)
- Monitoring, logging, and observability (Datadog, Prometheus, Kibana, or similar)
- Managed data platforms (Databricks or similar — administering and scaling, not just consuming)
- Network infrastructure fundamentals: load balancers, DNS, auto-scaling, multi-region topologies, proxies
- Security and access management: least-privilege, secrets management, controls for data systems
- MLOps concepts or tooling — a plus
What we value above technical skills
We are explicitly willing to trade depth in data tooling for the right operational character. Specifically:
- Humility — you don't know everything, you say so, and you ask before acting in unfamiliar territory
- Methodical execution — you minimize variables, you don't premature-optimize, you finish what you started before starting something new
- Communication — you tell the team what you're doing before you do it, especially in shared or production environments
- Ownership — when something goes wrong, you look inward first
- Independence – you can drive projects end-to-end, from ambiguous requirements to high quality deliverables. But you aren’t afraid to ask for help.
Benefits:
- Total compensation ($190,000 - $240,000)
- Equity compensation
- Health insurance coverage for you and your dependents
- 401K, FSA, and commuter benefits
- $150 monthly spending account
- $1,000 annual continued education benefit
- $500 Newbie Productivity Perk
- Unlimited PTO and sick days
- Monthly Company Wellness Day Off
- Snacks, drinks, and catered lunches at the office
- Team building events
- Hybrid RTO of 2 days per week in office.
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..
#LI-HYBRID
About Tatari
Frequently Asked Questions
How do I apply for the Staff Data Platform Engineer position at Tatari?
Use the Apply button above to submit your application directly to Tatari. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Staff Data Platform Engineer position at Tatari located?
This position is based in San Francisco, California. Tatari has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
How much does the Staff Data Platform Engineer role at Tatari pay?
Tatari has posted a compensation range of $190k to $240k for this position. Final offers typically vary based on candidate experience, location, and internal salary bands.
When was the Staff Data Platform Engineer role at Tatari posted?
This role was posted on July 9, 2026 (6 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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