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Remote Ai Data Engineer Jobs in Tennessee (NOW HIRING)

Remote micro1 is engaging Business Document Experts (Excel, PowerPoint, Word) to participate in a ... Familiarity with conversational interactions or prompt engineering with language models is a plus ...

$99K - $119K/yr

As a Data Engineer/Analyst, you will work closely with Medisolv clients to extract, transform and ... Work with modern Azure-based technologies and contribute to data-driven and AI-enhanced initiatives ...

Senior Data Engineer

Franklin, TN · Remote

$102K - $138K/yr

Remote-USA Revecore is embarking on re-architecting and modernizing its core platform. The Data ... The Senior Data Engineer will join the Technology function, solving complex data problems for the ...

Senior Applied AI Engineer

Nashville, TN · On-site +1

$100K - $138K/yr

You will work closely with data engineering and business teams to deliver scalable, intelligent ... This position's work style is remote from any of the locations listed below. You must reside in ...

Senior Applied AI Engineer

Nashville, TN · On-site +1

$100K - $138K/yr

You will work closely with data engineering and business teams to deliver scalable, intelligent ... This position's work style is remote from any of the locations listed below. You must reside in ...

Senior Applied AI Engineer

Nashville, TN · On-site +1

$100K - $138K/yr

You will work closely with data engineering and business teams to deliver scalable, intelligent ... This position's work style is remote from any of the locations listed below. You must reside in ...

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Remote Ai Data Engineer information

What are some common challenges faced by Remote AI Data Engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What is a Remote AI Data Engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

What are the key skills and qualifications needed to thrive as a Remote AI Data Engineer, and why are they important?

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.
What are popular job titles related to Remote Ai Data Engineer jobs in Tennessee? For Remote Ai Data Engineer jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Remote Ai Data Engineer jobs in Tennessee look for? The top searched job categories for Remote Ai Data Engineer jobs in Tennessee are:
What cities in Tennessee are hiring for Remote Ai Data Engineer jobs? Cities in Tennessee with the most Remote Ai Data Engineer job openings:
Infographic showing various Remote Ai Data Engineer job openings in Tennessee as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.
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 15 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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