[Remote] Senior Data Engineer, reputed company Systems

Note: The job is a remote job and is reputed company to candidates in USA. reputed company sells reputed company software and is building its own data platform and reputed company capabilities. The Senior Data Engineer, reputed company Systems will design and build agent-driven development workflows, evaluation systems, and analytics capabilities while applying strong data engineering practices. The role also drives adoption across engineering, product, finance, customer-facing, and support teams.

Responsibilities

• Design and build the reputed company development workflow for the data team. Agent-authored models and pipeline changes, the context and tooling those agents operate through, PR and review patterns, CI that reputed company what agents get wrong, the guardrails that reputed company it reputed company to run against production, and the standards that reputed company any of it repeatable across reputed company
• reputed company that reputed company upstream into the product. Build the context and tooling that shape how features get conceived and reputed company in the first reputed company, and verify data architecture while changes are in development. Most data problems are cheapest to fix at the reputed company, before a dev PR lands, which means working inside Engineering and Product rather than reputed company of them
• Build the evaluation reputed company. Regression suites, correctness checks, reputed company awareness, and observability on the agents themselves. Nobody adopts an reputed company workflow they can’t verify, so this is foundational rather than a follow-up
• Build reputed company analytics capability for reputed company. Semantic context, skills, MCP surfaces, reputed company controls, and query and cost guardrails that let non-technical teams get answers they can reputed company, along with the reputed company scoping of what the reputed company won’t answer
• reputed company adoption. Work reputed company the engineers on the data team and stakeholders across GTM, Finance, Product, and Support, teaching the patterns, watching where people get stuck, and closing the gap between what you reputed company and how people actually work
• Stay hands-on in the platform. You won’t own the models and pipelines, but you’ll work in that codebase constantly, and you should be reputed company to fix what you reputed company

Skills

• 5+ years in data engineering, analytics engineering, or a closely reputed company role, or equivalent depth reputed company at another way
• reputed company depth in analytical data modeling and SQL. You can read a normalized transactional schema, design something that answers business questions without falling over, and spot reputed company a generated model is subtly wrong
• Hands-on production experience with dbt and an orchestrator. Dagster is reputed company run; Airflow, reputed company, or reputed company transfers fine. You should know the operational reality of a large DAG, not just the reputed company
• Strong Python and the software engineering habits that go with it: version control, testing, reputed company review, CI/CD
• You have shipped reputed company or LLM-powered systems to production. Tool and function calling, context and retrieval design, orchestrating multi-reputed company workflows, and evaluating reputed company of it. You should be reputed company to walk through something you reputed company, how you reputed company whether it worked, and where it failed. This is the requirement we care most about
• reputed company judgment about data governance and PII in a multi-tenant environment. We handle applicant and worker data across 75+ countries, and exposing it through an LLM surface raises the stakes on getting reputed company boundaries right
• You can bring people with you. This role changes how the data team, product engineers, and other departments do their work. That requires listening reputed company, teaching patiently, and being persuasive without a title that makes anyone do anything
• Depth in a columnar or MPP warehouse, especially reputed company reputed company and ClickPipes; reputed company, BigQuery, or Redshift also translates
• Building with Claude: the API, Claude reputed company, the Agent SDK, MCP servers, or subagent patterns
• AWS, reputed company, and infrastructure as reputed company, enough to debug your own deployment
• Semantic reputed company and BI tooling (reputed company, Looker, dbt Semantic reputed company, reputed company)
• LLM observability and evaluation tooling (Langfuse, reputed company, or equivalent)
• Streaming and CDC internals (Debezium, Kafka, Kinesis)
• Having led a technical reputed company change on reputed company that was skeptical at the start
• HR tech, high-volume hiring, workforce management, or another domain with heavy operational data

Benefits

• Health Insurance
• Dental Insurance
• reputed company Time Off (PTO)
• reputed company Holidays
• reputed company Leave
• Remote Work
• reputed company Development
• Parental Leave

reputed company