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Databricks Engineer Jobs in Massachusetts (NOW HIRING)

Deloitte

Databricks Manager

Boston, MA · On-site +1

These solutions are powered by engineering for business advantage, transforming mission-critical ... Experience with Databricks MLOps or infrastructure setup * Experience coordinating delivery teams ...

Deloitte

Databricks Manager

Boston, MA · On-site

Bachelor's degree 6+ years of experience delivering data engineering, analytics, or cloud data platform solutions 3+ years of experience with Databricks and Apache Spark 3+ years of experience with ...

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Databricks Engineer information

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$65K

$121.9K

$221.7K

How much do databricks engineer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for databricks engineer in Massachusetts is $121,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,900.00 and $144,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior engineers in high-demand fields such as software engineering, data engineering, and specialized roles like Databricks Engineers can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership responsibilities. Compensation often includes base salary, bonuses, and stock options, particularly in large tech companies or startups with significant funding.

Is it hard to get hired at Databricks?

Getting hired as a Databricks Engineer can be competitive, as the role requires strong skills in big data technologies, cloud platforms, and programming languages like Python or Scala. Candidates often need relevant experience, certifications, and a solid understanding of data engineering concepts to succeed in the hiring process.

What is the salary of engineer in Databricks?

The salary of a Databricks Engineer 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 company size and industry demand.

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 career choice with good job prospects.

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.

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 Massachusetts? For Databricks Engineer jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Massachusetts look for? The top searched job categories for Databricks Engineer jobs in Massachusetts are:
What cities in Massachusetts are hiring for Databricks Engineer jobs? Cities in Massachusetts with the most Databricks Engineer job openings:
Databricks Engineer jobs near you

Information Technology_USA - USA_Developer

SysMind Tech

Boston, MA • On-site

$57.25 - $73.75/hr

Contractor

Posted 24 days ago

Job description

**Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
Bill Rate: market rate-market rate/hr
MSP Owner: Kelly Gosciminski
Location: Boston, MA - onsite
Duration: 6 months
GBaMS ReqID: 10538201
A Databricks Developer with Java expertise designs, builds, and maintains large-scale data processing solutions and AI/ML platforms, primarily using Java and Apache Spark on the Databricks platform. The role involves developing scalable data pipelines, optimizing Spark jobs, and ensuring data governance and security within cloud environments like AWS or Azure.
Core Responsibilities
• Data Pipeline Development: Design, develop, and maintain scalable ETL/ELT processes and data pipelines using Java and Spark on Databricks.
• Performance Optimization: Implement and tune Spark jobs to enhance performance, stability, and cost-efficiency in distributed systems, troubleshooting issues like data skew and memory errors.
• Cloud Integration: Work closely with cloud-native services (AWS/Azure IAM, Storage, Networking) and integrate Databricks offerings within the cloud infrastructure.
• Automation & CI/CD: Develop automation capabilities using Java APIs and Infrastructure-as-Code (IaC) tools like Terraform for platform provisioning, orchestration, and monitoring.
• Collaboration & Support: Partner with data scientists, ML engineers, and business teams to gather requirements, define compute needs, and provide support for production environments.
• Governance & Security: Enforce data governance policies, security standards (RBAC, encryption), and compliance requirements using tools like Unity Catalog and Delta Lake.
• Code Quality: Write clean, efficient, high-quality Java code following best practices, including participating in code reviews.
Required Skills & Qualifications
• Programming Languages: Strong proficiency in Java (Java 8 or higher) and experience with Spark fundamentals (DataFrames, SQL, RDDs).
• Big Data Technologies: Hands-on experience with Databricks workspace management, clusters, jobs, Delta Lake, MLflow, and Unity Catalog.
• Cloud Platforms: Deep understanding of a major cloud provider's infrastructure, such as AWS or Azure.
• Tools & Methodologies: Experience with CI/CD pipelines (GitHub Actions, Azure DevOps), Terraform, monitoring tools (Grafana, Prometheus), and Agile methodologies.
• Experience: Typically requires 5+ years of experience in software or data engineering.
• Certifications: A Databricks Certified Professional Data Engineer certification may be required or preferred.
Technical Requirements.
• Programming Languages Java, J2EE
• Cloud Technologies AWS, Azure
• Frameworks Struts, Spring, Springboot, Microservices, Kafka, spark
• Databases Oracle, MySQL, MongoDB, HBase and DB2.
• Web/App Servers WebLogic, Tomcat, WebSphere.
• Web Technologies ReactJS / Angular
• Build/ETL Tool Maven, Jenkins, Pentaho, Databricks
Role Descriptions: A Databricks Developer with Java expertise designs| builds| and maintains large-scale data processing solutions and AIML platforms| primarily using Java and Apache Spark on the Databricks platform. The role involves developing scalable data pipelines| optimizing Spark jobs| and ensuring data governance and security within cloud environments like AWS or Azure. Core ResponsibilitiesData Pipeline Development Design| develop| and maintain scalable ETLELT processes and data pipelines using Java and Spark on Databricks.Performance Optimization Implement and tune Spark jobs to enhance performance| stability| and cost-efficiency in distributed systems| troubleshooting issues like data skew and memory errors.Cloud Integration Work closely with cloud-native services (AWSAzure IAM| Storage| Networking) and integrate Databricks offerings within the cloud infrastructure.Automation CICD Develop automation capabilities using Java APIs and Infrastructure-as-Code (IaC) tools like Terraform for platform provisioning| orchestration| and monitoring.Collaboration Support Partner with data scientists| ML engineers| and business teams to gather requirements| define compute needs| and provide support for production environments.Governance Security Enforce data governance policies| security standards (RBAC| encryption)| and compliance requirements using tools like Unity Catalog and Delta Lake.Code Quality Write clean| efficient| high-quality Java code following best practices| including participating in code reviews. Required Skills QualificationsProgramming Languages Strong proficiency in Java (Java 8 or higher) and experience with Spark fundamentals (DataFrames| SQL| RDDs).Big Data Technologies Hands-on experience with Databricks workspace management| clusters| jobs| Delta Lake| MLflow| and Unity Catalog.Cloud Platforms Deep understanding of a major cloud providers infrastructure| such as AWS or Azure.Tools Methodologies Experience with CICD pipelines (GitHub Actions| Azure DevOps)| Terraform| monitoring tools (Grafana| Prometheus)| and Agile methodologies.Experience Typically requires 5 years of experience in software or data engineering.Certifications A Databricks Certified Professional Data Engineer certification may be required or preferred. Technical Requirements.Programming LanguagesJava| J2EECloud Technologies AWS| AzureFrameworksStruts| Spring| Springboot| Microservices| Kafka| sparkDatabasesOracle| MySQL| MongoDB| HBase and DB2.WebApp Servers WebLogic| Tomcat| WebSphere.Web TechnologiesReactJS AngularBuildETL ToolMaven| Jenkins| Pentaho| Databricks
Essential Skills: A Databricks Developer with Java expertise designs| builds| and maintains large-scale data processing solutions and AIML platforms| primarily using Java and Apache Spark on the Databricks platform. The role involves developing scalable data pipelines| optimizing Spark jobs| and ensuring data governance and security within cloud environments like AWS or Azure. Core ResponsibilitiesData Pipeline Development Design| develop| and maintain scalable ETLELT processes and data pipelines using Java and Spark on Databricks.Performance Optimization Implement and tune Spark jobs to enhance performance| stability| and cost-efficiency in distributed systems| troubleshooting issues like data skew and memory errors.Cloud Integration Work closely with cloud-native services (AWSAzure IAM| Storage| Networking) and integrate Databricks offerings within the cloud infrastructure.Automation CICD Develop automation capabilities using Java APIs and Infrastructure-as-Code (IaC) tools like Terraform for platform provisioning| orchestration| and monitoring.Collaboration Support Partner with data scientists| ML engineers| and business teams to gather requirements| define compute needs| and provide support for production environments.Governance Security Enforce data governance policies| security standards (RBAC| encryption)| and compliance requirements using tools l

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