Senior Data Platform Automation Engineer Remote

Bring more to life. At Danaher, our work saves lives. And each of us plays a part. Fueled by our culture of continuous improvement, we turn ideas into impact – innovating at the speed of life.  Our 60,000+ associates work across the globe at more than 15 unique businesses within life sciences, diagnostics, and biotechnology.   Are you ready to accelerate your potential and make a real difference?

At Danaher, you can build an incredible career at a leading science and technology company, where we’re committed to hiring and developing from within. You’ll thrive in a culture of belonging where you and your unique viewpoint matter.  Learn about the Danaher Business System which makes everything possible.

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, Fin Ops 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 Service Now catalogs and “data product in a box” templates.

Build and maintain enterprise CI/CD capabilities for Snowflake objects, dbt, Matillion, and Airflow using Git Hub Actions/Git Lab, 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, Lang Graph, 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, Data Ops, Dev Ops/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 Git Hub Actions or Git Lab;

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 (Lang Graph, Auto Gen); familiar with RAG, tool calling, and multi-agent orchestration. Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline (or equivalent experience). Travel, Motor Vehicle Record & Physical/Environment Requirements:
Ability to travel up to…