Databricks Data Engineer
Atlanta, GA
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign and maintain ETL/ELT pipelines using Azure Data Factory, Databricks and Spark
Build medallion-style (bronze, silver, gold) data models
Implement Delta Lake storage and Unity Catalog governance
Optimize Spark jobs for performance and cost efficiency
Implement data quality checks and validation frameworks
From the employer’s posting
Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, Databricks and Apache Spark
Develop scalable data models following medallion architecture (bronze, silver, gold layers)
Implement Delta Lake architecture for reliable data storage and processing
Optimize Spark jobs for performance and cost efficiency
Implement data quality checks and validation frameworks
What you’ll bring
All qualificationsCore experience
- 5+ years in data engineering, analytics, or software development
- 3+ years hands-on with the Databricks platform
- Strong experience with Apache Spark and PySpark
- Advanced SQL, including query optimization and performance tuning
- Bachelor's degree in Computer Science, IT or related field
Qualification wording
5+ years of progressive experience in data engineering, analytics, or software development
3+ years of hands-on experience with Databricks platform
Strong experience with Apache Spark and PySpark
Advanced SQL (query optimization, performance tuning)
Bachelor's degree in Computer Science, Information Technology or related field
Education & alternatives
Education/Experience: - Bachelor's degree in Computer Science, Information Technology or related field - 5+ years of progressive experience in data engineering, analytics, or software development
Tools in this posting
- Python
- Scala
- SQL
- Azure
- Databricks
- Delta Lake
- MLflow
- Power BI
- Spark
- SQL Server
- SSRS
- Terraform
- NumPy
- pandas
- PySpark
Source — Tool mentions in context
- Programming & Development: - Advanced Python programming (PySpark, pandas, NumPy) - Advanced SQL (query optimization, performance tuning)
- Advanced SQL (query optimization, performance tuning) - Scala programming (preferred) - Git version control and collaborative development
- Unity Catalog for data governance and cataloging - Databricks SQL and SQL Analytics - Databricks Workflows, Delta Live Tables, and job orchestration
- Advanced Python programming (PySpark, pandas, NumPy) - Advanced SQL (query optimization, performance tuning) - Scala programming (preferred)
- Data warehousing and data modeling concepts - SQL Server, including SSIS (Integration Services) - MLflow for ML lifecycle management (plus)
Overview The Databricks Data Engineer will be part of the Data Services team and help transform the delivery of data driven insights at scale. In this role, they will design and engineer robust data pipelines using technologies like Databricks, Azure Data Factory, Apache Spark, and Delta Lake. This role will work hands on crafting healthcare data solutions - processing massive healthcare datasets, optimizing performance, and ensuring our data is accurate, secure, and accessible when it matters most. Essential Functions
- Translate business requirements into technical specifications and document solution designs, data flows and architecture - Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, Databricks and Apache Spark - Implement Delta Lake architecture for reliable data storage and processing
- Collaborate with BI developers, data analysts, and data scientists - Design and implement data orchestration workflows using Azure Data Factory to coordinate complex ETL/ELT processes - Develop and maintain CI/CD pipelines for data workflows
- Cloud Technologies: - Azure Databricks - Cloud storage services (ADLS Gen2, Azure Blob Storage)
- Azure Databricks - Cloud storage services (ADLS Gen2, Azure Blob Storage) - Azure Data Factory for pipeline orchestration and integration
- Cloud storage services (ADLS Gen2, Azure Blob Storage) - Azure Data Factory for pipeline orchestration and integration - Experience designing and managing Azure Data Factory pipelines, triggers, and linked services
- Azure Data Factory for pipeline orchestration and integration - Experience designing and managing Azure Data Factory pipelines, triggers, and linked services - Infrastructure as Code (Terraform)
- Data quality and validation framework implementation - CI/CD pipeline development for data workflows (Azure DevOps) - Performance tuning and cost optimization
- Databricks Lakehouse Fundamentals - Azure Data Engineer Associate (DP-203) - Apache Spark certifications
- Implement Delta Lake architecture for reliable data storage and processing - Build and optimize data workflows using Databricks Workflows and Jobs - Develop scalable data models following medallion architecture (bronze, silver, gold layers)
- Implement Unity Catalog for data governance, access control, and metadata management - Create and maintain Databricks notebooks for data transformation and analysis - Optimize Spark jobs for performance and cost efficiency
Technical Skills: - Databricks Platform: - Expert-level knowledge of Databricks Workspace, clusters, and notebooks
- Databricks Platform: - Expert-level knowledge of Databricks Workspace, clusters, and notebooks - Delta Lake implementation and optimization
- Databricks SQL and SQL Analytics - Databricks Workflows, Delta Live Tables, and job orchestration - Delta Live Tables (DLT) for pipeline orchestration and data quality
- 5+ years of progressive experience in data engineering, analytics, or software development - 3+ years of hands-on experience with Databricks platform - Strong experience with Apache Spark and PySpark
Licenses/Certification: - Databricks Certified Data Engineer Associate (strongly preferred) - Databricks Certified Data Engineer Professional
- Databricks Certified Data Engineer Associate (strongly preferred) - Databricks Certified Data Engineer Professional - Databricks Lakehouse Fundamentals
- Databricks Certified Data Engineer Professional - Databricks Lakehouse Fundamentals - Azure Data Engineer Associate (DP-203)
- Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, Databricks and Apache Spark - Implement Delta Lake architecture for reliable data storage and processing - Build and optimize data workflows using Databricks Workflows and Jobs
- Expert-level knowledge of Databricks Workspace, clusters, and notebooks - Delta Lake implementation and optimization - Unity Catalog for data governance and cataloging
- Databricks Workflows, Delta Live Tables, and job orchestration - Delta Live Tables (DLT) for pipeline orchestration and data quality - Programming & Development:
- SQL Server, including SSIS (Integration Services) - MLflow for ML lifecycle management (plus) - Preferred Additional Skills
- Business Intelligence & Analytics: - Experience with BI tools (Power BI, SSRS) - Data warehousing and data modeling concepts
- Create and maintain Databricks notebooks for data transformation and analysis - Optimize Spark jobs for performance and cost efficiency - Implement data quality checks and validation frameworks
- 3+ years of hands-on experience with Databricks platform - Strong experience with Apache Spark and PySpark - Healthcare IT or healthcare data experience preferred
- Azure Data Engineer Associate (DP-203) - Apache Spark certifications We Offer
- Experience designing and managing Azure Data Factory pipelines, triggers, and linked services - Infrastructure as Code (Terraform) - Business Intelligence & Analytics:
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 25, 2026 · 36 days ago
- Recorded sightings
- 173
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
Overview
The Databricks Data Engineer will be part of the Data Services team and help transform the delivery of data driven insights at scale. In this role, they will design and engineer robust data pipelines using technologies like Databricks, Azure Data Factory, Apache Spark, and Delta Lake. This role will work hands on crafting healthcare data solutions - processing massive healthcare datasets, optimizing performance, and ensuring our data is accurate, secure, and accessible when it matters most.
Essential Functions
- Translate business requirements into technical specifications and document solution designs, data flows and architecture
- Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, Databricks and Apache Spark
- Implement Delta Lake architecture for reliable data storage and processing
- Build and optimize data workflows using Databricks Workflows and Jobs
- Develop scalable data models following medallion architecture (bronze, silver, gold layers)
- Implement Unity Catalog for data governance, access control, and metadata management
- Create and maintain Databricks notebooks for data transformation and analysis
- Optimize Spark jobs for performance and cost efficiency
- Implement data quality checks and validation frameworks
- Collaborate with BI developers, data analysts, and data scientists
- Design and implement data orchestration workflows using Azure Data Factory to coordinate complex ETL/ELT processes
- Develop and maintain CI/CD pipelines for data workflows
- Monitor data pipeline performance and troubleshoot issues
- Document data processes, architectures, and best practices
- Ensure compliance with data security and privacy regulations
- Provide support for new and existing solutions
About You
Knowledge/Skills/Abilities/Expectations:
- Excellent problem-solving and analytical skills
- Strong oral and written communication abilities
- Self-motivated with ability to adapt to new technologies quickly
- Team player with ability to work independently
- Detail-oriented with strong organizational skills
- Ability to manage multiple priorities and meet deadlines
- Experience communicating technical concepts to non-technical stakeholders
Technical Skills:
- Databricks Platform:
- Expert-level knowledge of Databricks Workspace, clusters, and notebooks
- Delta Lake implementation and optimization
- Unity Catalog for data governance and cataloging
- Databricks SQL and SQL Analytics
- Databricks Workflows, Delta Live Tables, and job orchestration
- Delta Live Tables (DLT) for pipeline orchestration and data quality
- Programming & Development:
- Advanced Python programming (PySpark, pandas, NumPy)
- Advanced SQL (query optimization, performance tuning)
- Scala programming (preferred)
- Git version control and collaborative development
- Cloud Technologies:
- Azure Databricks
- Cloud storage services (ADLS Gen2, Azure Blob Storage)
- Azure Data Factory for pipeline orchestration and integration
- Experience designing and managing Azure Data Factory pipelines, triggers, and linked services
- Infrastructure as Code (Terraform)
- Business Intelligence & Analytics:
- Experience with BI tools (Power BI, SSRS)
- Data warehousing and data modeling concepts
- SQL Server, including SSIS (Integration Services)
- MLflow for ML lifecycle management (plus)
- Preferred Additional Skills
- Experience with complex data modeling including dimensional modeling, star/snowflake schemas
- Experience with medallion architecture (bronze/silver/gold layers)
- Data quality and validation framework implementation
- CI/CD pipeline development for data workflows (Azure DevOps)
- Performance tuning and cost optimization
- DataOps and DevOps practices
Education/Experience:
- Bachelor's degree in Computer Science, Information Technology or related field
- 5+ years of progressive experience in data engineering, analytics, or software development
- 3+ years of hands-on experience with Databricks platform
- Strong experience with Apache Spark and PySpark
- Healthcare IT or healthcare data experience preferred
Licenses/Certification:
- Databricks Certified Data Engineer Associate (strongly preferred)
- Databricks Certified Data Engineer Professional
- Databricks Lakehouse Fundamentals
- Azure Data Engineer Associate (DP-203)
- Apache Spark certifications
We Offer
- Comprehensive Benefits Package: Health Insurance, 401k Plan, Tuition Reimbursement, PTO
- Opportunity to participate in a Fleet Program
- Competitive Salaries
- Mileage Reimbursement
- Professional growth and development opportunities
Legalese
- This is a safety-sensitive position
- Employee must meet minimum requirements to be eligible for benefits
- Where applicable, employee must meet state specific requirements
- We are proud to be an EEO employer
- We maintain a drug-free workplace
Location
GentivaOur Company
At Gentiva, it is our privilege to offer compassionate care in the comfort of wherever our patients call home. We are a national leader in hospice care, palliative care, home health care, and advanced illness management, with nearly 600 locations and thousands of dedicated clinicians across 38 states.
Our place is by the side of those who need us – from helping people recover from illness, injury, or surgery in the comfort of their homes to guiding patients and their families through the physical, emotional, and spiritual effects of a serious illness or terminal diagnosis.
Our nationwide reach is powered by a family of trusted brands that include:
- Hospice care: Gentiva Hospice, Emerald Coast Hospice Care, Heartland Hospice, Hospice Plus, New Century Hospice, Regency SouthernCare, SouthernCare Hospice Services, SouthernCare New Beacon
- Palliative care: Empatia Palliative Care, Emerald Coast Palliative Care
- Home health care: Heartland Home Health
- Advanced illness management: Illumia Health
With corporate headquarters in Atlanta, Georgia, and providers delivering care across the U.S., we are proud to offer rewarding careers in a collaborative environment where inspiring achievements are recognized – and kindness is celebrated.
Source details
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Atlanta, GA
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