Data Engineer

Quantum Technologies LLC; Houston (TX); On-site; USD 110,000 - 170,000; Full time

Job summary

Quantum Technologies. LLC in Houston is seeking a seasoned Databricks Engineer to design, develop, and optimize Spark-based data pipelines.

You will work with Spark DataFrames, Spark SQL, PySpark, and SQL to process large volumes of data in Azure Databricks, ensuring robust performance and scalable lakehouse solutions. You will monitor live Databricks jobs, troubleshoot issues, and collaborate with DevOps to manage Docker/Kubernetes deployments.

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.

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

Spark SQL

PySpark

SQL

Azure Databricks

Databricks Job Orchestration

Databricks Serverless

Streaming

ETL/ELT

Data Warehousing

Kubernetes

Docker

Scala

Java

Tools

Docker

Kubernetes

Job description

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

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.