# Senior Software Engineer - Observe by Snowflake, Streaming Data Products

**Company:** [Snowflake](https://hotfix.jobs/companies/snowflake)
**Location:** Menlo Park, CA
**Role:** Backend Engineering
**Salary:** $200k – $288k/yr
**Experience:** 7+ years
**Skills:** Go, SQL, Apache Iceberg, Stream Processing, Data Pipelines, Distributed Systems, APIs, Schema Design, Materialized Views, Data Modeling
**Posted:** 2026-05-08

> Owns streaming data products including APIs, schemas, and abstractions for tables/views unifying telemetry at petabyte scale. Requires 7+ years experience in databases/stream processing, Go proficiency, and architectural expertise in data systems.

## Job Description

## Responsibilities

- Own the data modeling product surface — the APIs, schemas, and abstractions through which customers create tables, views, and materialized views that unify their telemetry for correlation and querying, designed for high-performance execution at scale
- Design the right abstractions for how customers create and manage queryable data — from streaming materialized views to reference tables to log-derived metrics — each serving different needs but composing under one coherent, evolvable model
- Define freshness and staleness semantics that let customers trust their materialized views are current, and design the controls to tune the trade-off between query latency and compute cost
- Design APIs with strong schema taste: versioning, backwards compatibility, polymorphic data models, and clean contracts between systems
- Drive requirements and shape the execution engine based on what the product surface needs
- Layer complexity so an SRE gets a useful table from opinionated defaults in minutes, while a data engineer can express multi-stage pipelines with custom joins, windowing, and time-based aggregations
- Lead a team technically — setting architectural direction, writing production code, and mentoring engineers

## Requirements

- 7+ years of software engineering experience with deep expertise in databases, SQL, stream processing, or data pipeline systems
- Deep knowledge of data processing or streaming internals — late-arriving data, backfill and reprocessing on schema changes, event-time vs. processing-time semantics — with experience building products and applications on top of them
- Demonstrated experience designing and shipping APIs with strong taste in DB schema design, versioning, and developer ergonomics
- An architect's mental model — you think in systems, interfaces, contracts, and long-term evolution rather than short-term hacks
- A strong sense of user empathy and product intuition — you think beyond APIs and care about how customers define and query their data
- Proficiency in Go or another systems language, with ability to write production-grade distributed systems code

## Nice-to-Haves

- Experience building customer-facing data modeling or pipeline authoring products
- Hands-on experience with streaming semantics in production: watermarks, windowing, ordering, delivery guarantees, late-arriving data
- Background in designing or extending query languages, schema DSLs, or transformation DAG semantics
- Prior work building internal data platforms that turned raw event streams into curated, queryable tables for internal teams
- Familiarity with Apache Iceberg, open table formats, or data lakehouse architectures

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