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Databricks Engineer Jobs in Kentucky (NOW HIRING)

... Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies that meet the current and future business needs - Developing and documenting data ...

You will collaborate with product, engineering, EA Activation, security, data, and operations. You ... Hands-on architecture across Azure services and Snowflake/Databricks (data lake/data platform ...

You will collaborate with product, engineering, EA Activation, security, data, and operations. You ... Hands-on architecture across Azure services and Snowflake/Databricks (data lake/data platform ...

You will collaborate with product, engineering, EA Activation, security, data, and operations. You ... Hands-on architecture across Azure services and Snowflake/Databricks (data lake/data platform ...

Required Skills - ETL testing, Databricks, Strong in Cloud testing The Test Lead/Tester evaluates the software products according to the business standards or function requirements. The Test Lead ...

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Databricks Engineer information

See Kentucky salary details

$51.7K

$97K

$176.3K

How much do databricks engineer jobs pay per year?

As of Jul 12, 2026, the average yearly pay for databricks engineer in Kentucky is $96,955.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,900.00 and $115,100.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior Databricks Engineers with extensive experience, specialized skills in big data, cloud platforms, and advanced analytics can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or with significant bonuses and stock options. Such compensation typically requires a combination of technical expertise, leadership roles, and years of industry experience.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for expertise in big data processing, Spark, and cloud environments. Companies seek professionals skilled in data pipeline development, ETL processes, and cloud tools like AWS or Azure, making this a strong job market for qualified candidates.

What are some common challenges faced by Databricks Engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, or data engineering may earn higher compensation. Salaries can also vary based on industry demand and certifications held.

Is Databricks a high paying job?

A Databricks Engineer typically earns a high salary due to the specialized skills required in cloud computing, big data processing, and Spark platform expertise. Compensation varies based on experience, location, and certifications, but it is generally above average for data engineering roles.

What is a Databricks Engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

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

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.
What are popular job titles related to Databricks Engineer jobs in Kentucky? For Databricks Engineer jobs in Kentucky, the most frequently searched job titles are:
What cities in Kentucky are hiring for Databricks Engineer jobs? Cities in Kentucky with the most Databricks Engineer job openings:
Data Engineer - Manager

Data Engineer - Manager

Pwc

Louisville, KY • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 7 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

20th of 58 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Analyse and identify the linkages and interactions between the component parts of an entire system.
Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
Develop skills outside your comfort zone, and encourage others to do the same.
Effectively mentor others.
Use the review of work as an opportunity to deepen the expertise of team members.
Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
As part of the Data and Analytics Engineering team you can design and implement thorough data architecture strategies that meet current and future business needs. As a Manager you can lead the development of data models, support compliance with data governance policies, and collaborate with business stakeholders to translate data requirements into technical solutions. You can also build and enhance ETL/ELT pipelines, manage data warehouses and data lakes, and implement data security practices.
Responsibilities
- Design and implement thorough data architecture strategies
- Lead the development of data models
- Achieve compliance with data governance policies
- Collaborate with business stakeholders to translate data requirements
- Build and enhance ETL/ELT pipelines
- Manage data warehouses and data lakes
- Implement data security leading practices
- Foster a culture of data-driven decision making
What You Must Have
- Bachelor's Degree in Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics
- 5 years of experience
What Sets You Apart
- Certification in Cloud Platforms [e.g., AWS Solutions Architect, AWS Data Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions Architect, Azure Data Engineer Associate, or Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus
- Designing and implementing thorough data architecture strategies that meet the current and future business needs
- Developing and documenting data models, data flow diagrams, and data architecture guidelines
- Verifying data architecture is compliant with data governance and data security policies
- Collaborating with business stakeholders to understand their data requirements and translate them into technical solutions
- Evaluating and recommending new data technologies and tools to enhance data architecture
- Building, maintaining, and improving ETL/ELT pipelines for data ingestion, processing, and storage across batch and real-time data processing
- Building, maintaining, and improving Data Quality rules leveraging DQ tools and/or other ETL/ELT tools
- Developing and deploying scalable data storage solutions using AWS, Azure and GCP services such as S3, Amazon RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud Storage etc.
- Implementing data integration solutions using AWS Glue, AWS Lambda, Azure Data Factory, Azure Functions, GCP Functions, GCP Dataproc, Dataflow and other relevant services
- Designing and managing data warehouses and data lakes, verifying data is organized and accessible
- Monitoring and troubleshooting data pipelines, data warehouses and workflows to verify data quality, system reliability, performance and cost management
- Implementing IAM roles and policies to manage access and permissions within AWS, Azure, GCP
- Use AWS CloudFormation, Azure Resource Manager templates, Terraform for infrastructure as code (IaC) deployments
- Use AWS, Azure and GCP DevOps services to build and deploy DevOps pipelines
- Implementing data security practices using AWS, Azure, GCP, Snowflake or Databricks
- Improving Cloud resources for cost, performance, and scalability
- Proficiency in SQL and experience with relational databases
- Proficient in programming languages such as Python, Java, or Scala
- Familiarity with big data technologies like Hadoop, Spark, or Kafka is a plus
- Experience with machine learning and data science workflows is a plus
- Knowledge of data governance and data security practices
- Demonstrating analytical, problem-solving, and communication skills
- Having the ability to work independently and as part of a team in a fast-paced environment
- Applying modern, cloud-based technology skills, ability to research emerging trends, analyst publications, and adoption of modern technologies in solution architectures
- Collaborating and contributing as a team member: understanding personal and team roles, contributing to a positive working environment by building proven relationships with team members, proactively seeking guidance, clarification and feedback
- Prioritizing and handling multiple tasks, researching and analyzing pertinent client, industry and technical matters, utilizing problem-solving skills, and communicating effectively in written and verbal formats to various audiences (including various levels of management and external clients) in a professional business environment
- Coaching and collaborating with associates who assist with this work, including providing coaching, feedback and guidance on work performance

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $99,000 - $232,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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