Data Engineer

Compunnel, Inc.; Oakland (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Compunnel, Inc. is seeking a Data Engineer to modernize enterprise data platforms in Oakland, CA. You will focus on migrating Oracle PL/SQL ETL processes to Azure Databricks and building scalable cloud-based data pipelines.

The role emphasizes data quality, reliability, and performance, with collaboration across stakeholders and production support to optimize workloads.

Qualifications

• Bachelor's degree or higher in CS/IS/Engineering or related field.
• 4–6 years of ETL, data engineering, or database development experience.
• 4+ years of advanced SQL development and query optimization.
• 3+ years of Oracle PL/SQL development experience.
• 3+ years of Azure Databricks development experience.
• Experience migrating legacy ETL to cloud-based platforms.
• Strong knowledge of Spark SQL, PySpark, Delta Lake, and ADLS.
• Familiarity with Git, source control, and CI/CD processes.
• Excellent communication and collaboration skills.

Responsibilities

• Governs requirements gathering from stakeholders.
• Analyzes Oracle SQL/PL/SQL ETL for migration.
• Migrates ETL workflows to Azure Databricks using Spark SQL and PySpark.
• Designs, develops, tests, deploys, and maintains data pipelines.
• Creates technical design documents and data mappings.
• Validates migrated data with business users.
• Converts Oracle PL/SQL logic into Databricks pipelines.
• Performs data validation and reconciliation between sources and targets.
• Monitors, troubleshoots, and enhances production ETL pipelines.
• Optimizes pipeline performance and resolves production issues.
• Participates in source control, CI/CD, and release management.
• Manages assigned projects and delivers high-quality solutions.

Skills

ETL engineering

SQL development

Azure Databricks

Spark SQL

PySpark

Delta Lake

ADLS

Communication

Problem-solving

Team collaboration

Education

Bachelor's degree in Computer Science / Information Systems / Engineering

Tools

Git

CI/CD

Job description

We are seeking a Data Engineer with expertise in Azure Databricks to support the modernization of enterprise data platforms. The ideal candidate will have experience migrating Oracle PL/SQL-based ETL processes to Databricks, developing scalable cloud-based data pipelines, and ensuring data quality, reliability, and performance.

Key Responsibilities

• Gather business and technical requirements from stakeholders.
• Analyze Oracle SQL and PL/SQL ETL processes for migration.
• Migrate Oracle ETL workflows to Azure Databricks using Spark SQL and PySpark.
• Design, develop, test, deploy, and maintain scalable data pipelines.
• Create technical design documents and data mappings.
• Validate migrated data with business users and SMEs.
• Convert complex Oracle PL/SQL logic into Databricks pipelines.
• Perform data validation and reconciliation between source and target systems.
• Monitor, troubleshoot, and enhance production ETL pipelines.
• Optimize pipeline performance and resolve production issues.
• Participate in source control, CI/CD, and release management activities.
• Manage assigned projects and deliver high-quality solutions.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 4–6 years of experience in ETL, database development, or data engineering.
• 4+ years of advanced SQL development and query optimization.
• 3+ years of Oracle PL/SQL development experience.
• 3+ years of Azure Databricks development experience.
• Experience migrating legacy ETL processes to cloud-based data platforms.
• Strong experience with Spark SQL, PySpark, Delta Lake, and Azure Data Lake Storage (ADLS).
• Experience with Git, source control, and CI/CD processes.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience in healthcare, biomedical research, or clinical data environments.
• Experience converting Oracle PL/SQL packages, procedures, and functions into Databricks pipelines.
• Experience with Azure Data Factory or Databricks Workflows.
• Knowledge of dimensional data modeling and enterprise data warehousing.
• Experience with Python.
• Experience with Power BI or Tableau.
• Familiarity with AI or machine learning-enabled data engineering solutions.