Data engineer

Robotic Technologies Automation; Quincy (MA); On-site; USD 80,000 - 106,000; Full time

Job summary

Robotic Technologies Automation is seeking a Data Engineer in Quincy, MA to lead the design, development and optimization of large-scale data pipelines using Azure Databricks. The role focuses on Spark jobs, streaming, lakehouse architectures and performance tuning across Databricks environments.

The ideal candidate has hands-on experience with PySpark/Scala, SQL, and cluster configuration, with familiarity in DevOps pipelines, Azure services, and container orchestration (Docker/Kubernetes).

Qualifications

• 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.

Responsibilities

• Develop and optimize Spark jobs, data transformations, and processing workflows.
• Implement Azure Databricks streaming and transformation solutions.
• Design and implement data warehouse/lakehouse solutions.
• Monitor and debug live Databricks jobs.

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.