Hybrid Data Engineer: Modeling & Pipelines Architect

ExcelGens, Inc.; East Hanover (NJ); Hybrid; USD 110,000 - 140,000; Full time

Job summary

ExcelGens, Inc. in East Hanover, NJ is seeking a Data Engineer specializing in database design, data modelling, SQL, ETL, and data pipelines to support analytics applications.

You will design and maintain data models, gather requirements, develop ETL processes, ensure data quality, and collaborate with BI developers and product owners.

Hybrid work arrangement with cross-functional teams and data governance responsibilities.

Qualifications

• 3+ years of database design experience.
• 1+ year of data engineering/data modeling experience.
• Strong SQL experience.
• Experience with ETL and data pipelines.
• Experience with data modeling and data quality/profiling.
• Experience with multiple data sources; SAP experience is a plus.
• Bachelor's degree in Computer Science, Information Systems, or related field.

Responsibilities

• Design and maintain data models, databases, and data pipelines.
• Gather business requirements and translate them into technical data solutions.
• Develop and support ETL/data integration processes.
• Analyze data sources for accuracy, completeness, integrity, and reliability.
• Develop UAT/SIT test cases and support testing.
• Show data governance, data quality, and metadata management.
• Work with Product Owners, BI Developers, Data Engineers, and business stakeholders.
• Create technical documentation and communicate technical concepts clearly.

Skills

Database design

Data engineering

Data modelling

SQL

ETL

Data quality/profiling

SAP experience

Education

Bachelor's degree in Computer Science, Information Systems, or related field

Tools

Python / PySpark

Azure

GCP

Databricks

Power BI / Tableau / Alteryx

CI/CD / DataOps

Job description

ExcelGens, Inc. in East Hanover, NJ is seeking a Data Engineer specializing in database design, data modelling, SQL, ETL, and data pipelines to support analytics applications.

You will design and maintain data models, gather requirements, develop ETL processes, ensure data quality, and collaborate with BI developers and product owners.

Hybrid work arrangement with cross-functional teams and data governance responsibilities.