Data Engineer

DataJobs; Montvale (NJ); Hybrid; USD 83,000 - 99,000; Full time

Job summary

DataJobs in Montvale, NJ is seeking a data engineer for a hybrid role focused on production stability, incident resolution, and Azure data engineering.

Responsibilities include supporting data pipelines, building notebook workflows in PySpark with Databricks, and optimizing data warehouses with T-SQL.

Qualifications

• 5+ years of experience in data or data-platform troubleshooting or technical leadership.
• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• Hands-on Azure data engineering and Python experience.
• Working knowledge of Databricks and PySpark.
• Advanced T-SQL with data warehouse experience, including indexing and query tuning.
• Experience troubleshooting ETL pipelines, data-quality issues, and performance bottlenecks.
• Understanding of RDBMS concepts, reporting flows, and production support practices.
• Strong incident ownership and stakeholder communication.

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 and improve data reliability.

Skills

Azure data engineering

Python

Databricks

PySpark

T-SQL

data warehouse concepts

root-cause analysis

Education

Bachelor’s degree in Computer Science or related field

Tools

Azure Data Factory

Delta

Parquet

Notebooks

AKS

SSIS

MSBI

Power BI

Alteryx

ADLS

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