Data Engineer
Python
Aks
Analytics
Azure
Azure Data Factory
Azure Data Platform
Big Data
Bigdata
Business Analytics
Business Intelligence
Cloud
Cloud Data Engineering
Cloud Data Platform
Cloud Platform
Cloud Platforms
Cloud Platforms Cloud Platforms
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Engineering
Data Factory
Data Factory Azure
Data Integration
Data Lake
Data Lakehouse
Data Pipeline
Data Platform
Data Processing
Data Visualization
Data Warehouse
Database
Databases
Databricks
Delta Lake
Digital Marketing
Engineer
ETL
Hr Technology
Informatica
Information Technology (IT)
Microsoft
Microsoft Azure
Microsoft Office
Office Tools
Power BI
Power Platform
Programming
Programming Language
Programming Languages
Pyspark
Reporting and Analytics
Spark
SQL
Job Description
Support and modernize production data systems in a hybrid role focused on stability, troubleshooting, and Azure data engineering.
Responsibilities
- Support and troubleshoot data pipelines, large datasets, and production data incidents
- Develop and maintain solutions in Azure data engineering using Python and Databricks
- Build and manage notebook-based workflows for data transformations and read/write operations in PySpark
- Optimize data warehouse performance using advanced T-SQL, including indexing and query tuning
- Collaborate with stakeholders to resolve incidents, conduct root-cause analysis, and improve data reliability
Requirements
- 5+ years of experience in application support, technical leadership, or data-platform troubleshooting
- Bachelor’s degree in Computer Science, Information Systems, or a related field
- Hands-on experience with Azure data engineering and Python
- Working knowledge of Databricks and PySpark
- Advanced T-SQL and data warehouse experience, including stored procedures, functions, execution plans, indexing, and query optimization
- Experience troubleshooting ETL pipelines, data-quality issues, performance bottlenecks, and scalability issues
- Understanding of RDBMS concepts, reporting flows, data movement, and production support practices
- Strong incident ownership, root-cause analysis, stakeholder communication, and technical coaching skills
Tools & Technologies
- Azure: Azure Data Factory, ADLS
- Data & Processing: Databricks, PySpark, Delta, Parquet, Notebooks
- Databases & Querying: T-SQL
- Related Platforms: AKS, SSIS, MSBI, Power BI, Alteryx
- Data Sources: ERP extraction
- Domain Data: audit and accounting-related data
Schedule & Work Setting
- Monday to Friday
- Standard business hours
- Hybrid work: at least 3 days onsite; Tues to Thurs are mandatory
Location
- Montvale, NJ (hybrid)
Compensation
- USD 60–72 per hour
Desired Skills
- Experience with Azure Data Factory and ADLS
- Delta/Parquet and AKS experience
- SSIS/MSBI, Power BI, and Alteryx experience
- ERP extraction concepts
- Audit and accounting-related data experience
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