Azure Data Platform Engineer | SQL, Python & ETL

Orion Innovation; Montvale (NJ); On-site; USD 120,000 - 160,000; Full time

Job summary

Orion Innovation is seeking an experienced data-platform professional to support and lead data initiatives. You will work with Azure data engineering, Python, Databricks, and PySpark to transform and manage data workflows.

Strong SQL and data warehousing skills are essential, with a focus on production reliability. The role requires incident ownership, root-cause analysis, and coaching of teammates while optimizing ETL pipelines and data movement across enterprise systems.

Qualifications

• 5+ years of experience in application support, technical leadership, or data-platform troubleshooting.
• Aws? not included; Azure data engineering and Python experience with Databricks and PySpark.
• Advanced T-SQL and data warehouse skills including stored procedures, functions, and query optimization.
• Experience troubleshooting ETL pipelines, large datasets, data-quality issues, and performance bottlenecks.
• Strong incident ownership, root-cause analysis, and stakeholder communication.

Responsibilities

• Own incident management and root-cause analysis for data-platform issues.
• Coach team members and coordinate cross-functional data engineering tasks.
• Optimize ETL pipelines, data movement, and production data quality and performance.

Skills

Python

Azure data engineering

Data platform troubleshooting

Root-cause analysis

Stakeholder communication

Technical coaching

ETL pipelines

Data quality

Education

Bachelor's degree in Computer Science or related field

Tools

Azure Data Factory

ADLS

Delta/Parquet

AKS

SSIS/MSBI

Power BI

Alteryx

Job description

Orion Innovation is seeking an experienced data-platform professional to support and lead data initiatives. You will work with Azure data engineering, Python, Databricks, and PySpark to transform and manage data workflows.

Strong SQL and data warehousing skills are essential, with a focus on production reliability. The role requires incident ownership, root-cause analysis, and coaching of teammates while optimizing ETL pipelines and data movement across enterprise systems.