Senior Software Engineer (Observe by Snowflake, Data Management)

• We are hiring a Senior Software Engineer for Observe by Snowflake on the Data Management team

• This team is responsible for the tables, views, and materialized views at the core of Observe’s architecture

• Observe’s data lake approach lets customers correlate heterogeneous telemetry — logs, metrics, traces, events — across a unified data model

• This role owns that data model: how customers define, shape, and query the semi-structured data that makes cross-signal correlation low-latency and cost-efficient, at petabyte scale, over continuous streaming telemetry

• 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

• Observe’s data modeling surface — how customers go from raw telemetry to structured, queryable, correlated data — has proven successful and is now at an inflection point, growing rapidly in richness and complexity to serve evolving enterprise needs

• Your architectural decisions will shape how this surface scales — serving thousands of teams, supporting new abstraction types, and maintaining coherence as the platform matures

• And you’ll do it backed by Snowflake’s query engine and data platform, with the ownership culture and shipping velocity of a small focused team

Benefits

• Comprehensive health insurance plans

• Health savings accounts

• Robust retirement plans

• Life and disability insurance

• Weekly online lunch and learns

• Virtual workout classes

• Ergonomic work-from-home equipment

• On-demand mental health and wellness programs

• Fertility benefits and family planning resources

• Generous time-off and various leave plans

• Onsite and Remote Work

• Employee discounts and pre-tax selections

• New hire equity + Employee Stock Purchase Plan (ESPP)

• Quarterly bonus or commission program- Demonstrated experience designing and shipping APIs with strong taste in DB schema design, versioning, and developer ergonomics

• A strong sense of user empathy and product intuition — you think beyond APIs and care about how customers define and query their data

• An architect’s mental model — you think in systems, interfaces, contracts, and long-term evolution rather than short-term hacks

• 5+ years of software engineering experience with deep expertise in databases, SQL, stream processing, or data pipeline systems

• Proficiency in Go or another systems language, with ability to write production-grade distributed systems code

• 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

• 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