Big Data Engineer - Nashville, TN - Hybrid Preferred / Remote accepted

2. Cloud Technology/HDFS big data ecosystem experience - bringing data sources into GCP, transforming and loading to databases; ETL at scale.
3. Microsoft SQL or Postgres (advanced features) - strong development experience required, not just querying familiarity. Nice to have:

• Kubernetes exp -Dagster

• It's replacing their current pipeline orchestration setup
• It runs on Azure Kubernetes Service (AKS), so Docker/Kubernetes experience pairs well with it
• It's a newer, niche platform - he doesn't expect candidates to have it, but said if you come across someone with Dagster experience, "that'd be somebody I'd be interested in meeting with"
• Not a hard requirement, but a significant differentiator

• The Data Management team needs a senior-level engineer who can operate independently, design and build GCP-based data solutions, and mentor junior developers - all within a fast-paced, matrixed Agile environment. The team is scaling its enterprise data capability and needs someone who can own technically complex work end-to-end with minimal supervision.

Who is the internal customer that this role is ultimately supporting:

• Data scientists, business analysts, and IT and business leaders across the enterprise who rely on structured, semi-structured, and unstructured data pipelines for analysis, reporting, and AI/ML use cases.

Differentiators for the opportunity ("sizzle"):

1. Fully remote if need be. Onsite preferred. Note* if remote, no chance of conversion.
2. High-visibility enterprise role - this person sets technical direction for a group of applications and shapes the GCP data architecture across the organization.
3. AI/ML integration scope - not just plumbing data; this role analyzes business requirements and designs AI/ML-based solutions, giving strong engineers a path to meaningful, cutting-edge work. Job Descripti Overview: Responsibilities: Build and support a GCP-based ecosystem for enterprise-wide analysis of structured, semi-structured, and unstructured data Bring new data sources into GCP/HDFS, transform and load to databases Design, develop, deploy, and support software systems with minimal supervision Analyze requirements and design AI/ML-based solutions; integrate those solutions for customer environments Support regular data movement between clusters; manage production support SLAs Collaborate with data scientists, business analysts, and IT/business leaders to understand data needs and use cases Lead and mentor junior developers; take responsibility for technically robust, end-to-end solutions Work within Agile practices and principles across a mixed consultant/employee team

Bachelor's degree in Computer Science, Software Engineering, or related field Production-level Python development experience Strong experience with ETL processes or analytics/reporting applications Experience with Microsoft Azure or AWS (GCP is the primary platform in use) Advanced Microsoft SQL or Postgres development experience Solid expertise developing modern, scalable applications Preferred: GCP / HDFS big data ecosystem experience (active platform - strong differentiator) AI/ML solution design and integration HL7 or other healthcare integration experience Supply chain or healthcare industry background