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Remote Data Processing Jobs in Tennessee (NOW HIRING)

Data Engineer - Hybrid / Remote

Brentwood, TN · On-site +1

$108.30K - $130.10K/yr

Remote option available for candidates outside of surrounding areas. This role requires a highly ... Architect and implement scalable data processing pipelines using: * Databricks Runtime (Apache ...

Data Engineer - Hybrid / Remote

Brentwood, TN · On-site +1

$108.30K - $130.10K/yr

Remote option available for candidates outside of surrounding areas. This role requires a highly ... Architect and implement scalable data processing pipelines using: * Databricks Runtime (Apache ...

Lead Data Engineer

Nashville, TN · Remote

$99K - $130.40K/yr

... processes that support the meaningful work of community oncologists and the patients they serve ... remote. Our team members are all individually motivated, yet collaborative. We maintain a high ...

... grows and its data processing needs change. We strive to provide our customers with software ... We do not offer full-time remote positions, candidates must be able to commute to the office or be ...

Remote-USA Revecoreis embarking on re-architecting and modernizing its core platform. The Data ... Build and maintain automated data validation and monitoring processes to proactively detect and ...

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Remote Data Processing information

See Tennessee salary details

$11

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How much do remote data processing jobs pay per hour?

As of May 31, 2026, the average hourly pay for remote data processing in Tennessee is $18.39, according to ZipRecruiter salary data. Most workers in this role earn between $14.62 and $20.29 per hour, depending on experience, location, and employer.

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

To thrive as a Remote Data Processing specialist, you need strong analytical skills, attention to detail, and proficiency in data entry and management, often supported by a relevant degree or experience in data-related roles. Familiarity with databases, spreadsheet software like Microsoft Excel or Google Sheets, and sometimes data processing tools such as SQL or Python is typically required. Excellent time management, self-motivation, and clear communication are essential soft skills for remote collaboration and meeting deadlines. These abilities ensure data accuracy, efficient processing, and effective teamwork in a remote work environment.

What are some common challenges faced by professionals in remote data processing roles, and how can they be overcome?

Remote data processing professionals often encounter challenges such as ensuring data accuracy, managing large datasets, and maintaining clear communication with distributed teams. To overcome these, it's important to establish strong data validation protocols, use reliable tools for data management, and schedule regular virtual meetings to stay aligned with team objectives. Additionally, setting clear expectations and using collaborative platforms can help mitigate misunderstandings and improve workflow efficiency.

What is remote data processing?

Remote data processing refers to the collection, analysis, and management of data from a location outside of a traditional office setting, often using cloud-based tools and remote access technologies. Professionals in this role handle data entry, validation, organization, and sometimes basic analytics, ensuring data integrity and accessibility for organizations. This job typically requires strong computer skills, attention to detail, and the ability to work independently while maintaining data security and privacy protocols.

What is the difference between Remote Data Processing vs Remote Data Analysis?

AspectRemote Data ProcessingRemote Data Analysis
Primary RoleHandling data input, cleaning, and preparationInterpreting data to generate insights and reports
Skills & CertificationsData management, SQL, basic scriptingStatistical analysis, data visualization, tools like Excel, R, Python
Work EnvironmentData warehouses, cloud platforms, databasesAnalysis tools, dashboards, reporting software
Industry UsageData management teams, IT departmentsBusiness intelligence, marketing, finance

Remote Data Processing focuses on preparing and managing raw data, while Remote Data Analysis involves interpreting that data to inform decisions. Both roles often require similar technical skills but differ in their core responsibilities and end goals.

What are the most commonly searched types of Data Processing jobs in Tennessee? The most popular types of Data Processing jobs in Tennessee are:
What job categories do people searching Remote Data Processing jobs in Tennessee look for? The top searched job categories for Remote Data Processing jobs in Tennessee are:
What cities in Tennessee are hiring for Remote Data Processing jobs? Cities in Tennessee with the most Remote Data Processing job openings:
Data Engineer - Hybrid / Remote

Data Engineer - Hybrid / Remote

Surgery Partners

Brentwood, TN • On-site, Remote

$108.30K - $130.10K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 17 days ago


Surgery Partners rating

7.5

Company rating: 7.5 out of 10

Based on 78 frontline employees who took The Breakroom Quiz

217th of 864 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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