Senior Databricks Developer

Quantum Technologies LLC; Pennsylvania; On-site; USD 96,000 - 131,000; Full time

Job summary

Quantum Technologies. LLC is seeking a Senior Databricks Developer in Malvern, PA to design, build, and optimize enterprise-grade data pipelines using Databricks, PySpark, Python, and SQL.

You will work within AWS to deliver scalable, production-ready data platforms, applying Delta Lake and Medallion architectures. The role emphasizes hands-on engineering, with a focus on building robust ingestion, transformation, and orchestration solutions, monitoring, and operational support across large

Responsibilities

• Design, develop, and maintain large-scale ETL/ELT pipelines using Databricks, PySpark, Python, and SQL.
• Build scalable data ingestion, transformation, and orchestration frameworks within AWS.
• Develop and support Delta Lake implementations and Medallion Architecture (Bronze, Silver, Gold) data pipelines.
• Create and optimize batch and streaming pipelines processing large volumes of data.
• Leverage AWS services (S3, Glue, Lambda, EMR, IAM, EventBridge, CloudWatch, Kinesis, Redshift) to support end-to-end data workflows.
• Optimize Spark jobs, Delta tables, and Databricks workloads for performance and cost efficiency.
• Partner with Data Engineers, Architects, Analytics teams, and stakeholders to deliver high-quality data solutions.
• Implement data quality controls, monitoring, and operational support processes.
• Troubleshoot production issues across Databricks and AWS environments.

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: Senior Databricks Developer
Location: Malvern, PA
Duration: 12 Months + Extension
Bill Rate: $81/hour (C2C)
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Summary:

We are seeking a Senior Databricks Developer with 7+ years of Data Engineering experience and deep expertise in Databricks, AWS, PySpark, Python, and SQL. This is a highly technical, hands-on engineering role within a data engineering team focused primarily on building, enhancing, and supporting enterprise data pipelines. The ideal candidate will have extensive experience developing cloud-native data solutions in AWS, implementing Delta Lake and Medallion architectures, and delivering scalable, production-grade data pipelines using Databricks. This is not a consulting role; we are looking for a developer who enjoys building and optimizing data platforms and solving complex data engineering challenges.

Responsibilities:

• Design, develop, and maintain large-scale ETL/ELT pipelines using Databricks, PySpark, Python, and SQL.
• Build scalable and highly reliable data ingestion, transformation, and orchestration frameworks within AWS.
• Develop and support Delta Lake implementations and Medallion Architecture (Bronze, Silver, Gold) data pipelines.
• Create and optimize batch and streaming pipelines that process large volumes of structured and unstructured data.
• Leverage AWS services including S3, Glue, Lambda, EMR, IAM, EventBridge, CloudWatch, Kinesis, and Redshift to support end-to-end data workflows.
• Optimize Spark jobs, Delta tables, and Databricks workloads for performance, scalability, and cost efficiency.
• Partner with Data Engineers, Architects, Analytics teams, and business stakeholders to deliver high-quality data solutions.
• Implement data quality controls, monitoring, alerting, and operational support processes.
• Troubleshoot and resolve complex production issues across Databricks and AWS environments.
• Contribute to engineering best practices, code reviews, automation, and platform modernization initiatives.

Required Qualifications:

• 7+ years of Data Engineering experience building enterprise-scale data platforms and pipelines.
• 5+ years of hands-on Databricks development experience in production environments.
• Strong expertise in Python, PySpark, and SQL with a focus on pipeline development.
• Extensive experience developing and supporting data pipelines within AWS.
• Strong knowledge of Delta Lake, Lakehouse Architecture, and Medallion Architecture (Bronze, Silver, Gold).
• Hands-on experience with AWS services such as S3, Glue, Lambda, EMR, Redshift, Kinesis, IAM, and CloudWatch.
• Deep understanding of Spark architecture, distributed data processing, performance tuning, partitioning, and optimization.
• Experience building highly scalable batch and streaming data processing solutions.
• Strong understanding of data modeling, data warehousing concepts, and modern data architectures.
• Experience supporting production environments, monitoring data pipelines, and troubleshooting complex data issues.

Preferred Qualifications:

• Experience with Databricks Workflows, Delta Live Tables (DLT), Unity Catalog, and Structured Streaming.
• Experience with Kafka, Airflow, or cloud-native orchestration frameworks.
• Experience implementing CI/CD pipelines using GitHub Actions, Jenkins, or Azure DevOps.
• Infrastructure as Code experience utilizing Terraform or CloudFormation.
• Databricks Certified Data Engineer Associate or Professional certification.
• Experience working within large enterprise AWS environments supporting mission-critical data platforms.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.