Stravito

Senior Data Engineer

Vaga remota de Senior Data Engineer com fit claro de localização do candidato.

Publicada11 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

Resumo da vaga

Conteúdo da vaga extraído em seções para revisão mais rápida.

Build the foundation: Own the data platform that powers AI products used daily by thousands of professionals at Fortune 500 companies
Work with data that matters: Transform event streams, usage telemetry, and millions of proprietary market research documents into reliable, queryable intelligence
Solve hard infrastructure problems: Design multi-tenant, secure-by-default pipelines and APIs that meet the compliance bar of the world's most demanding enterprise customers
Own it end-to-end: This isn't a role where someone else defines the work. You'll scope work independently, dig into data quality issues, field requests from stakeholders, and drive things to completion.

Build and operate data pipelines that move event streams, document metadata, and usage data into our cloud data warehouse (ClickHouse Cloud, Snowflake, Azure)
Design and maintain APIs for analytics and event extraction, with multi-tenant security baked in (RBAC, OAuth, SSO/SAML)
Make data usable: whether that's modeling schemas for BI consumers, investigating a data quality issue, or helping a stakeholder understand what's possible with the data we have
Keep things reliable and secure through automated tests, monitoring, and handling of sensitive data within SOC 2 and ISO 27001 environments
Power our AI experiences by working with vector stores, indexing, and retrieval systems
Drive engineering best practices across the platform: CI/CD, peer reviews, infrastructure as code, API versioning, and clear documentation

A track record of building data platforms in SaaS or cloud-native analytics environments
Strong programming skills, with depth in at least one of Python or Kotlin and willingness to work across both. Experience with Rust or TypeScript is a plus
Hands-on experience with MPP/cloud data warehouses (e.g., ClickHouse, Redshift, BigQuery, Snowflake, Azure Synapse) and cloud infrastructure on AWS or Azure
Practical experience designing, consuming, and maintaining APIs
Familiarity with multi-tenant security patterns: RBAC, row-level security, and identity standards such as OAuth and SAML/SSO
Solid engineering fundamentals: CI/CD, automated testing, observability, and infrastructure as code (Terraform a plus)
Working knowledge of data privacy requirements (PII handling, GDPR) and experience operating within compliance frameworks like SOC 2 or ISO 27001

Experience integrating with BI tools (Power BI, Tableau, Looker)
Familiarity with semantic search, embeddings, or vector stores (e.g., Pinecone, pgvector)
Exposure to event-driven or streaming architectures (Kafka, Kinesis, SQS/SNS)
Experience with containerisation (Docker, ECS/Fargate)
Interest in leveraging LLMs and AI tooling to accelerate data engineering work
dbt, SQLMesh, or similar transformation framework experience

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