Member of Data Staff (Analytics Engineer) at Perplexity | chakrie

Requirements

Additional Requirements

6+ years of experience as an analytics engineer, data engineer, data scientist, or closely related role.
you can reason about correctness, performance, joins, grain, and edge cases in complex warehouse queries.
Strong data modeling experience - you've worked hands-on with dbt (or a similar transformation framework) in production, and you understand dimensional modeling, data contracts, testing, and how analytical schemas should evolve.
Pipeline ownership - you've built, maintained, debugged, and improved production data pipelines.
Warehouse management experience - you've worked with warehouse administration, access patterns, permissions, performance tuning, cost management, or operational ownership.
Governance mindset - you think clearly about data ownership, access controls, privacy, retention, lineage, auditability, and the risks of making data too easy to access.
AI-native working style - you already use AI to speed up development, documentation, QA, exploration, and repetitive workflow automation.
Stakeholder fluency - you know how to turn messy analytical requirements into trusted models, metrics, and reusable data assets.
Autonomy and execution - you can take projects from ambiguous problem to production-quality system with minimal oversight.
Operational judgment - you care about reliability, governance, security, cost, and long-term maintainability.
Snowflake administration, optimization, cost management, or warehouse performance tuning.
Experience with RBAC, PII handling, data classification, retention policies, audit workflows, or privacy/security reviews.
Experience with Databricks or other modern data infrastructure.
Experience building semantic layers, metrics layers, metadata systems, or data catalogs.
Python experience for data tooling, automation, orchestration, or quality checks.
Previous experience as an early analytics engineer or data engineer at a high-growth startup.
Own the foundation - your work will determine how fast and confidently the company can use data.
Build for humans and AI - the next generation of data infrastructure needs to be understandable by agents as well as analysts.
High leverage - better models, pipelines, and tools multiply every data scientist and every stakeholder who depends on data.
Small team, broad scope - you'll have room to define standards, choose tools, and ship systems that become company-wide defaults.

Responsibilities

A clear overview of what is expected, written by the people who posted it, with every detail you need to decide.

Qualifications, experience and the skills that matter most, along with anything that would make you stand out.

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Contact details, links to the official source and the notes our team adds after checking each listing by hand.

Skills & expertise

Qualifications, experience and the skills that matter most, along with anything that would make you stand out.

Practical next steps, the documents to prepare and the dates to keep in mind before you apply or get in touch.

Contact details, links to the official source and the notes our team adds after checking each listing by hand.

Everything else on this page, kept up to date and available to every member of Chakrie at no cost at all.

Salary & benefits

A clear overview of what is expected, written by the people who posted it, with every detail you need to decide.

Qualifications, experience and the skills that matter most, along with anything that would make you stand out.

Practical next steps, the documents to prepare and the dates to keep in mind before you apply or get in touch.

Contact details, links to the official source and the notes our team adds after checking each listing by hand.

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Member of Data Staff (Analytics Engineer)

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