Data Engineer

Compunnel, Inc.; San Jose (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Compunnel, Inc. is seeking an experienced Data Engineer to design, implement, and optimize cloud-based data solutions on Azure.

This role focuses on scalable pipelines, modern data platforms, and distributed computing with Spark, Databricks, and SQL. You will build and maintain Azure Databricks workflows, Data Lake architectures, and data models to support enterprise analytics, while producing architecture diagrams and documentation and collaborating with cross-functional teams in San Jose,

Qualifications

• Bachelor's degree in CS or related field.
• 5+ years hands-on data engineering with Spark, MapReduce, or Databricks.
• Experience designing cloud-based data solutions on Microsoft Azure.
• Strong Python and SQL skills.
• Experience with Azure Databricks, Data Lake, and cloud-native services.
• Ability to create architecture diagrams and documentation.

Responsibilities

• Design scalable cloud-based data pipelines, data warehouses, and data lakes.
• Develop cloud-native data architectures aligned with business objectives.
• Integrate Azure data services, including Azure Databricks and Data Lake.
• Build Spark-based ETL pipelines in Databricks.
• Develop data models to support analytics and reporting.
• Produce architecture diagrams and technical documentation.
• Monitor and optimize data pipeline performance and reliability.
• Collaborate with cross-functional teams to deliver scalable cloud-based data solutions.
• Ensure data security and governance best practices.

Skills

Distributed computing

Data modeling

Cloud architecture

Python

SQL

Documentation

Education

Bachelor's degree in Computer Science or related field

Tools

Azure Databricks

Databricks

Spark

Azure Data Lake

Hadoop

Visio/Lucidchart

Job description

We are seeking an experienced Data Engineer to design, implement, and optimize cloud-based data solutions on Azure. This role combines hands-on data engineering with cloud data architecture, focusing on scalable data pipelines, modern data platforms, and distributed computing technologies. The ideal candidate will have strong expertise in Azure, Databricks, Spark, SQL, Python, and cloud-native data services, with the ability to create clear technical documentation and architecture diagrams.

Key Responsibilities

• Design and implement scalable, secure cloud-based data pipelines, data warehouses, and data lakes.
• Develop and optimize cloud-native data architectures aligned with business objectives.
• Design and integrate Azure data services, including Azure Databricks and Azure Data Lake.
• Build, maintain, and optimize Spark-based ETL pipelines using Databricks.
• Develop robust data models to support enterprise analytics and reporting.
• Create and maintain architecture documentation, including data flow diagrams, entity-relationship diagrams, and system architecture diagrams.
• Produce technical documentation to support implementation, knowledge sharing, and governance.
• Monitor and optimize data pipeline performance, scalability, and reliability.
• Troubleshoot issues related to data pipelines, data quality, and data accessibility.
• Implement best practices for data security, governance, and cloud architecture.
• Collaborate with cross-functional teams to deliver scalable cloud-based data solutions.

Required Qualifications

• Bachelor's degree in Computer Science or a related field.
• 5+ years of hands-on data engineering experience using distributed computing technologies such as Spark, MapReduce, or Databricks.
• Proven experience designing and implementing cloud-based data solutions on Microsoft Azure.
• Strong hands-on experience developing Spark ETL pipelines in Azure Databricks.
• Deep understanding of data modeling concepts and techniques.
• Strong proficiency with relational and non-relational database systems.
• Advanced knowledge of Azure Databricks, Azure Data Lake, and cloud-native data services.
• Experience with big data technologies, including Hadoop and Spark.
• Strong scripting skills using Python and SQL.
• Experience creating technical diagrams using tools such as Microsoft Visio, Lucidchart, or similar diagramming tools.
• Strong understanding of data security, governance, and best practices.

Preferred Qualifications

• Experience with AI Agents or AI-enabled data solutions.
• Experience working with Gainsight.
• Strong analytical, problem-solving, and troubleshooting skills.
• Excellent communication and technical documentation skills.