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Mlops Engineer Remote Jobs in Tennessee (NOW HIRING)

Data Engineer - Hybrid / Remote

Brentwood, TN · On-site +1

$108K - $130K/yr

Data Engineer - Hybrid / Remote Opportunity * Hybrid for candidates in Nashville and surrounding ... Familiarity with MLOps workflows and Databricks MLflow * Experience using dbt with Databricks SQL

Data Engineer - Hybrid / Remote

Brentwood, TN · On-site +1

$108K - $130K/yr

Data Engineer - Hybrid / Remote Opportunity * Hybrid for candidates in Nashville and surrounding ... Familiarity with MLOps workflows and Databricks MLflow * Experience using dbt with Databricks SQL

Pre-Sales Leader

Nashville, TN · On-site +1

$100K - $175K/yr

Pre-Sales Leader/Pre-Sales Engineer- Banking industry Location: Near Nashville, TN (Remote/Hybrid ... MLOps environments * SQLMesh * AI-powered productivity tools and workflows Why Consider This ...

Pre-Sales Leader

Nashville, TN · On-site +1

$100K - $175K/yr

Pre-Sales Leader/Pre-Sales Engineer- Banking industry Location: Near Nashville, TN (Remote/Hybrid ... MLOps environments * SQLMesh * AI-powered productivity tools and workflows Why Consider This ...

Mlops Engineer Remote information

What are some common challenges faced by remote MLOps Engineers, and how can they be addressed?

Remote MLOps Engineers often encounter challenges related to communication and collaboration, especially when coordinating with data scientists, developers, and operations teams across different time zones. To overcome these challenges, it's essential to establish clear documentation practices, utilize collaborative platforms for workflow management, and schedule regular virtual meetings to ensure alignment. Additionally, maintaining strong version control and automated CI/CD pipelines helps streamline model deployment and monitoring, reducing friction caused by remote coordination. Building proactive communication habits and leveraging cloud-based tools can significantly improve efficiency and team cohesion.

What is the difference between Mlops Engineer Remote vs Data Engineer?

AspectMlops Engineer RemoteData Engineer
Required CredentialsBachelor's in CS, Data Science, or related; experience with cloud platforms and ML toolsBachelor's in CS, Data Engineering, or related; strong SQL and ETL skills
Work EnvironmentRemote, collaborative teams, cloud-based infrastructureRemote or on-site, data pipelines, cloud or on-premises systems
Industry UsageTech, AI, ML-focused companiesFinance, healthcare, tech, and other data-driven industries

While both roles involve working with data and cloud platforms, Mlops Engineers focus on deploying and maintaining machine learning models in production, often working remotely with ML-specific tools. Data Engineers primarily build and manage data pipelines and infrastructure. The roles overlap in cloud experience and data handling but differ in their core focus areas.

What does an MLOps Engineer do, especially in a remote role?

An MLOps Engineer is responsible for streamlining and automating the deployment, monitoring, and management of machine learning models in production environments. Working remotely, they collaborate with data scientists, software engineers, and IT teams using cloud-based tools to ensure that ML models are scalable, reliable, and maintainable. Their tasks often include setting up CI/CD pipelines for ML workflows, managing model versioning, and monitoring model performance over time. Remote MLOps Engineers leverage communication and project management tools to stay aligned with distributed teams and ensure seamless operations.

What are the key skills and qualifications needed to thrive as an MLOps Engineer (Remote), and why are they important?

To thrive as an MLOps Engineer, you need a solid background in machine learning, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS or Azure, as well as certifications in cloud services or DevOps, are highly valuable. Strong problem-solving, collaboration, and communication skills help you bridge the gap between data science and operations teams in a remote setting. These competencies are crucial for building scalable, reliable machine learning systems that deliver real-world value efficiently.
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Data Engineer - Hybrid / Remote

Data Engineer - Hybrid / Remote

Surgery Partners

Brentwood, TN • On-site, Remote

$108K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Surgery Partners rating

7.8

Company rating: 7.8 out of 10

Based on 83 frontline employees who took The Breakroom Quiz

131st of 890 rated healthcare providers


Job description

Data Engineer - Hybrid / Remote Opportunity

  • Hybrid for candidates in Nashville and surrounding areas.
  • Remote option available for candidates outside of surrounding areas. 

This role requires a highly technical Data Engineer with expert-level proficiency in Azure Databricks, distributed data pipelines, and large-scale healthcare data processing. This role focuses on designing and implementing high-throughput ingestion pipelines, transactional lakehouse layers, and secure PHI data flows using Azure-native services and Databricks runtime optimizations.

You will build and operate production-grade data pipelines that meet rigorous requirements for security, lineage, compliance (HIPAA), observability, and operational SLAs, supporting analytics, AI, and clinical insights across the organization.

Core Responsibilities

Platform & Architecture

  • Architect and implement scalable data processing pipelines using:
    • Databricks Runtime (Apache Spark, Spark SQL, MLflow, Delta Lake)
    • Delta Lake ACID transactions, Z-Ordering, OPTIMIZE, and Change Data Feed (CDF)
    • Unity Catalog for governance, lineage, RBAC, and audit controls
  • Design and enforce a medallion (Bronze/Silver/Gold) architecture with schema evolution, Delta Live Tables (DLT), and robust error-handling patterns
  • Build high-performance ingestion frameworks for:
    • FHIR and HL7 message streams
    • X12 837/835 healthcare claims data
    • EHR/EMR source systems
    • Batch, real-time, and event-driven data sources

Azure Cloud Engineering

  • Develop and operate data pipelines leveraging:
    • Azure Data Lake Storage Gen2 (hierarchical namespace, ACLs, POSIX permissions)
    • Azure Data Factory or Synapse Pipelines (parameterization, dynamic pipelines, triggers)
    • Azure Event Hubs and/or Service Bus for streaming ingestion
    • Azure SQL Database and Azure Synapse (Dedicated and Serverless pools)
    • Azure Functions for lightweight orchestration and automation
    • Azure Monitor, Log Analytics, and Application Insights for observability
  • Implement enterprise-grade security including:
    • VNet integration and private endpoints
    • Secrets and key management using Azure Key Vault
    • Managed identities and least-privilege access controls

Distributed Data Engineering

  • Develop optimized PySpark and/or Scala pipelines using advanced Spark techniques:
    • Catalyst optimizer tuning
    • Cluster sizing and autoscaling strategies
    • Adaptive Query Execution (AQE)
    • Efficient join strategies (broadcast vs. shuffle)
  • Build and maintain:
    • High-volume batch ETL pipelines (100M+ records)
    • Low-latency streaming pipelines using Spark Structured Streaming
  • Implement CI/CD for Databricks environments, including:
    • Git-integrated DEV/QA/PROD workspaces
    • Automated job and workflow deployments
    • Unit testing using pytest and Databricks testing frameworks

Healthcare Data & Compliance

  • Design and implement secure PHI pipelines compliant with:
    • HIPAA Privacy and Security Rules
    • SOC 2 and HITRUST-aligned controls
  • Build pipelines supporting healthcare data standards including:
    • FHIR R4 resources (Patient, Encounter, Observation, Claim, etc.)
    • HL7 v2.x messages (ADT, ORU, ORM)
    • X12 EDI transactions (837, 835, 270/271)
  • Ensure end-to-end lineage tracking, auditability, and data retention across all lakehouse layers

Required Qualifications

  • 5+ years of experience in modern data engineering roles
  • Expert-level proficiency in:
    • PySpark and Spark SQL
    • Databricks (Jobs, Workflows, Repos, Delta Live Tables)
    • Delta Lake architecture and transactional design patterns
    • Azure Data Factory or Azure Synapse Pipelines
    • Cloud-native data security (RBAC, ABAC, privilege boundary enforcement)
  • Strong experience working with healthcare data formats and standards:
    • FHIR (JSON)
    • HL7 v2/v3
    • X12 EDI claims data
  • Deep understanding of distributed systems, data partitioning strategies, concurrency, and cluster resource tuning

Preferred Qualifications

  • Experience implementing Unity Catalog at enterprise scale
  • Familiarity with MLOps workflows and Databricks MLflow
  • Experience using dbt with Databricks SQL
  • Relevant certifications, including:
  • Databricks Data Engineer Professional
  • Microsoft Azure DP-203
  • HL7 or FHIR certification (nice to have)

Benefits:

  • Comprehensive health, dental, and vision insurance
  • Health Savings Account with an employer contribution
  • Life Insurance 
  • PTO
  • 401(k) retirement plan with a company match
  • And more! 

ENVIRONMENTAL/WORKING CONDITIONS: Normal busy office environment with much telephone work. Possible long hours as needed. The description is intended to provide only basic guidelines for meeting job requirements. Responsibilities, knowledge, skills, abilities and working conditions may change as needs evolve.

*If you are viewing this role on a job board such as Indeed.com or LinkedIn, please know that pay bands are auto assigned and may not reflect the true pay band within the organization.

*No Recruiters Please


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