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Databricks Engineer Jobs in Parsippany, NJ (NOW HIRING)

P-1591 At Databricks, we are passionate about enabling data and AI teams to solve the world ... Founded by engineers - and customer obsessed - we leap at every opportunity to solve technical ...

Databricks Architect

Jersey City, NJ · On-site

$67.50 - $88.75/hr

This role is primarily focused on Databricks platform architecture, Infrastructure-as-Code (Terraform), and enterprise platform engineering. Strong AWS networking expertise is beneficial but is not ...

Showing results 41-60

Databricks Engineer information

See Parsippany, NJ salary details

$59.8K

$112.3K

$204.2K

How much do databricks engineer jobs pay per year?

As of Aug 11, 2026, the average yearly pay for databricks engineer in Parsippany, NJ is $112,264.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,000.00 and $133,200.00 per year, depending on experience, location, and employer.

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 architecture can earn higher compensation, often exceeding $160,000 per year.

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?

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.

Is a Databricks engineer in demand?

Databricks engineers are in high demand due to the growing adoption of cloud-based data analytics and machine learning platforms. They typically require skills in Spark, SQL, and cloud environments, and their roles are often available across various industries seeking data-driven solutions.
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Sr. Forward Deployed Engineer (FDE) - Manufacturing

Databricks

New York, NY

$114K - $157K/yr

Full-time

Re-posted 8 days ago


Job description

CSQ127R319

As a Sr. Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. 

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

The impact you will have:

  • Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
  • Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
  • Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
  • Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
  • Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
  • Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
  • Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
  • Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

  • 6+ years experience in data engineering, data platforms & analytics, or software engineering
  • Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
  • Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
  • Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals
  • Familiarity with CI/CD for production deployments
  • Working knowledge of MLOps, ML/AI models and AI APIs
  • Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
  • Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
  • Documentation and white-boarding skills.
  • Experience working with enterprise clients and managing conflicts across a broad stakeholder range
  • Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
  • Travel to customers 20% of the time
  • Databricks Certification