Senior Data Platform Automation Engineer - USA Remote

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The Senior Data Platform Automation Engineer engineers the automation, developer experience, and reliability layer of Danaher’s Enterprise Data Platform (Snowflake, Matillion, dbt, Airflow, Azure). This role treats the platform as code — delivering IaC, CI/CD, self-service golden paths, observability and auto-remediation, FinOps and compliance guardrails, and agentic AI operators using Azure AI Foundry and Anthropic Claude.

This position reports to the Director – Data Platform and Operations and is part of the Enterprise Data Engineering team located in United States (Remote) and will be fully remote.

In this role, you will have the opportunity to

Design, deploy, and manage Infrastructure-as-Code (IaC) solutions using Terraform/Pulumi for Snowflake, Azure, Matillion, and Airflow, including reusable golden-path modules, automated provisioning, drift detection, onboarding, access management, and self-service developer enablement through ServiceNow catalogs and “data product in a box” templates.

Build and maintain enterprise CI/CD capabilities for Snowflake objects, dbt, Matillion, and Airflow using GitHub Actions/GitLab, incorporating automated testing, environment promotion, deployment governance, rollback capabilities, and platform standardization.

Automate and optimize data platform operations through event-driven workflows, schema-drift detection, idempotent replay, backfill processing, controlled reprocessing, provisioning automation, and end-to-end operational reliability across the data ecosystem.

Develop and implement AI-driven platform operations and developer enablement solutions using Azure AI Foundry, Anthropic Claude, LangGraph, and/or Semantic Kernel to support L1 incident triage, self-healing workflows, cost optimization, developer copilots, governance guardrails, and model evaluation frameworks.

Establish platform observability, reliability, and operational excellence through unified telemetry, monitoring, SLO management, runbook-as-code practices, auto-remediation capabilities, and continuous reduction of mean time to resolution (MTTR) using Azure Monitor and Log Analytics.

The essential requirements of the job include

7+ years in data engineering, DataOps, DevOps/SRE, or platform engineering, with 4+ years automating cloud data platforms.

Hands-on across the modern data stack — Snowflake, Matillion, dbt, and Apache Airflow — with proven ability to automate ingestion, orchestration, and transformation.

Proven IaC and CI/CD experience using Terraform or Pulumi and GitHub Actions or GitLab; strong Python skills.

Hands-on with LLM/agent applications using Azure AI Foundry (Azure OpenAI, Prompt Flow), Snowflake Cortex, Anthropic Claude, OpenAI, or open-source frameworks (LangGraph, AutoGen); familiar with RAG, tool calling, and multi-agent orchestration.