Senior Data Engineer - Azure Databricks Lakehouse

VeeRteq Solutions Inc.; Philadelphia (Philadelphia County); Hybrid; USD 150,000 - 190,000; Full time

Job summary

VeeRteq Solutions Inc. is seeking a Senior Data Engineer in Philadelphia, PA, to design enterprise-scale data platforms on Azure and Databricks in a hybrid role.

You will lead the development and optimization of ETL/ELT pipelines, drive cloud modernization, and mentor data teams to follow best practices. This role collaborates with stakeholders and product teams to enable analytics, AI/ML initiatives, and data-driven decision making.

Qualifications

• Minimum 10+ years in data engineering.
• 7+ years with Azure Data Services.
• 5+ years with Azure Databricks.
• Experience leading enterprise cloud data modernization projects.
• Hands-on experience with Azure Databricks, ADLS Gen2, ADF, PySpark, Python, SQL, Delta Lake.

Responsibilities

• Design and build scalable data platforms, data lakes, and lakehouse solutions.
• Develop and optimize ETL/ELT pipelines using Azure and Databricks.
• Lead data architecture, data modeling, and cloud modernization initiatives.
• Mentor data engineering teams and establish best practices.
• Improve platform performance, security, and cost efficiency.
• Implement CI/CD, monitoring, and production support processes.
• Collaborate with business leaders, architects, analysts, and product teams.
• Support analytics, reporting, AI/ML, and data-driven business initiatives.

Skills

Data engineering

Team leadership

Agile/Scrum

Tools

Azure Databricks

ADLS Gen2

ADF

PySpark

Python

SQL

Delta Lake

Power BI

Git

Azure DevOps

Terraform

Azure Synapse Analytics

Kafka

Job description

VeeRteq Solutions Inc. is seeking a Senior Data Engineer in Philadelphia, PA, to design enterprise-scale data platforms on Azure and Databricks in a hybrid role.

You will lead the development and optimization of ETL/ELT pipelines, drive cloud modernization, and mentor data teams to follow best practices. This role collaborates with stakeholders and product teams to enable analytics, AI/ML initiatives, and data-driven decision making.