Senior Data Engineer

Stravito

2d•Remote

About The Position

Stravito transforms how Consumer Insights professionals and Brand Managers work by building AI that automates their core workflows. We help world-leading organizations across industries accelerate strategic decision-making by turning millions of market research documents into intelligent systems that generate reports, discover insights proactively, and synthesize knowledge across vast content libraries. The data platform underneath makes all of this possible: ingesting millions of documents, enforcing tenant-level security, and feeding the AI systems our customers rely on daily. This role is unique because you will build the foundation, owning the data platform that powers AI products used daily by thousands of professionals at Fortune 500 companies. You will work with data that matters, transforming event streams, usage telemetry, and millions of proprietary market research documents into reliable, queryable intelligence. You will solve hard infrastructure problems by designing multi-tenant, secure-by-default pipelines and APIs that meet the compliance bar of the world's most demanding enterprise customers. You will own it end-to-end, scoping work independently, digging into data quality issues, fielding requests from stakeholders, and driving things to completion.

Requirements

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.
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

Nice To Haves

Experience with Rust or TypeScript is a plus
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

Responsibilities

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