Data engineer

Quantum Technologies. LLC; Quincy (MA); On-site; USD 80,000 - 107,000; Full time

Job summary

Quantum Technologies. LLC in Quincy, MA seeks a Data Engineer to design and optimize Spark-based data pipelines on Azure Databricks, building scalable lakehouse architectures for large volumes of data.

The role focuses on streaming and batch transformations, Databricks job orchestration, and SQL tuning. Collaboration with analytics teams is essential; Docker/Kubernetes knowledge is a plus.

Qualifications

• Experience developing Spark jobs and data pipelines.
• Strong SQL skills and performance tuning experience.
• Experience with Azure Databricks and lakehouse architectures.

Responsibilities

• Develop and optimize Spark jobs, data transformations, and processing workflows.
• Implement complex data streaming and transformation solutions using Azure Databricks.
• Design and implement data warehouse/lakehouse solutions.
• Monitor, debug, and resolve issues in live Databricks jobs.
• Troubleshoot DevOps pipelines, Azure, and AKS services.
• Build data ingestion, streaming, and transformation solutions.

Skills

Apache Spark

Spark DataFrames

ETL/ELT

Azure Databricks

Databricks

Databricks Lakehouse

Structured Streaming

Data pipelines

Tools

Unity Catalog

Auto Loader

Databricks Serverless

Cluster Sizing

Job Orchestration

Job description

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

Job Title: Data engineer

Location: Quincy, MA

Duration: 14 Months

Bill Rate: $68/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 Description

Mandatory Technical Skills

• Apache Spark, Spark DataFrames, Notebooks and Spark SQL
• ETL/ELT and data pipeline development
• Scala/PySpark and SQL performance tuning
• Azure Databricks and large-volume data processing
• Databricks Expertise
• Unity Catalog
• Auto Loader
• Lakehouse and Medallion Architecture
• Databricks Serverless Options
• Dataset and DataFrame
• Cluster Configuration and Sizing
• Databricks Job Orchestration
• Spark Structured Streaming

Additional Responsibilities & Requirements

• Develop and optimize Spark jobs, data transformations, and processing workflows.
• Implement complex data streaming and transformation solutions using Azure Databricks.
• Design and implement data warehouse/lakehouse solutions.
• Monitor, debug, and resolve issues in live Databricks jobs.
• Troubleshoot DevOps pipelines, Azure, and AKS services.
• Build data ingestion, streaming, and transformation solutions.
• Experience with Apache Big Data technologies and languages such as PySpark, R, or Java is advantageous.
• Docker and Kubernetes experience is good to have.

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.