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Databricks Software Jobs in Pennsylvania (NOW HIRING)

SysMind Tech

Data Engineer - Databricks

Pittsburgh, PA · On-site

$108K - $130K/yr

Contract Role Overview We are seeking an experienced Data Engineer with strong expertise in Databricks, Python, and Spark to design and build scalable data pipelines. The ideal candidate will have ...

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Databricks Software information

What engineer makes $500,000 a year?

Senior software engineers, especially those working in high-demand fields like data engineering or cloud engineering at large tech companies, can earn $500,000 or more annually. These roles often require extensive experience, advanced skills in programming and cloud platforms, and may include bonuses or stock options that contribute to total compensation.

What is Databricks Software?

Databricks Software is a unified analytics platform built on Apache Spark that provides tools for big data processing, machine learning, and collaborative data science. It enables organizations to store, manage, and analyze large datasets efficiently, supporting both batch and streaming data workloads. Databricks also offers collaborative notebooks, automated workflows, and integrations with cloud storage and data lakes, making it a popular choice for data engineering, data science, and business analytics teams.

How much do Databricks employees make?

Salaries for Databricks software roles vary based on experience, location, and specific position, but the average annual salary for software engineers at Databricks typically ranges from $100,000 to $150,000. Senior roles and specialized skills in data engineering or cloud platforms can command higher compensation. Benefits often include stock options, bonuses, and professional development opportunities.

Is Databricks a high paying job?

Working as a Databricks software engineer or data scientist typically offers above-average salaries compared to other tech roles, reflecting the specialized skills in cloud platforms, big data, and Spark. Compensation varies based on experience, location, and certifications, but generally includes competitive base pay, bonuses, and stock options. These roles often require knowledge of programming languages like Python or Scala and familiarity with cloud environments such as AWS or Azure.

What are some common challenges faced by Databricks Software Engineers, and how can they be overcome?

Databricks Software Engineers often encounter challenges related to scaling big data pipelines, optimizing Spark workloads, and integrating diverse data sources. Navigating the complexity of distributed systems and managing cloud infrastructure can be demanding, especially when ensuring data reliability and security. To overcome these challenges, engineers typically collaborate closely with data scientists, DevOps, and platform teams, leverage Databricks' extensive documentation and community support, and adopt best practices such as version control and continuous integration. Regular knowledge sharing and staying updated with new features also help engineers succeed in this dynamic environment.

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

To thrive as a Databricks Software Engineer, you need strong programming skills in languages like Python, Scala, or Java, as well as a solid understanding of distributed computing and data engineering concepts. Familiarity with Databricks platform, Apache Spark, cloud services (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valued. Excellent problem-solving abilities, collaboration, and effective communication are important soft skills for this role. These skills ensure efficient development, deployment, and optimization of big data solutions that drive business insights and innovation.

What exactly are Databricks Jobs?

Databricks Jobs are automated tasks or workflows that run on the Databricks platform, typically involving data processing, machine learning, or analytics tasks. They can be scheduled, monitored, and managed through the Databricks workspace, requiring knowledge of Spark, SQL, or Python scripting. Job roles often involve configuring clusters and ensuring efficient execution of data pipelines.

What is the difference between Databricks Software vs Data Engineer?

AspectDatabricks SoftwareData Engineer
Primary RolePlatform for data analytics and machine learningBuilds, maintains data pipelines and infrastructure
Required SkillsSQL, Spark, cloud platforms, data science basicsSQL, ETL, programming (Python, Scala), database management
Work EnvironmentCloud-based, collaborative data platformData teams, cloud or on-premises environments
CertificationsDatabricks certifications, cloud certificationsNone specific, often cloud or data certifications

While Databricks Software provides a platform for data analytics and machine learning, Data Engineers focus on building and maintaining data pipelines and infrastructure. Both roles often work together but have distinct responsibilities and skill sets within the data ecosystem.

What are popular job titles related to Databricks Software jobs in Pennsylvania? For Databricks Software jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Databricks Software jobs in Pennsylvania look for? The top searched job categories for Databricks Software jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Databricks Software jobs? Cities in Pennsylvania with the most Databricks Software job openings:
Databricks Software jobs near you
Sr. Forward Deployed Engineer (FDE) - Healthcare & Life Sciences

Sr. Forward Deployed Engineer (FDE) - Healthcare & Life Sciences

Databricks

Philadelphia, PA • On-site

$99K - $137K/yr

Full-time

Posted 10 days ago

Job description

Job Summary:
Databricks is the data and AI company that empowers organizations through its Data Intelligence Platform. As a Sr. Forward Deployed Engineer (FDE), you will collaborate with customers to deliver production-grade data and AI solutions, leading architecture and design decisions while ensuring customer satisfaction and project success.
Responsibilities:
• 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
• 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
• Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• 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.
• Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.
Qualifications:
Required:
• 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
Company:
Databricks is a data and AI platform that unifies data engineering, analytics, and machine learning on a lakehouse architecture. Founded in 2013, the company is headquartered in San Francisco, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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