Data Engineer - Top Stack

NOTE: Our client will sponsor/transfer visas! This is not CTC. Direct hire!

Top Stack Group has been retained by a Fortune 250 company with offices in PA and NJ to identify a Data Engineer to join their Data Team. team. This is a full-time, salaried position with a competitive base salary, structured bonus and a comprehensive benefits package. This is a hybrid position (2 days per week in their Holmdel, NJ office and 3 days work from home)

In this Data Engineer position, you will be working in the ETL Services Group. Your focus would be on Data Reliability and you would be responsible for assisting in the design, development, and implementation of enterprise level data products for business analytics and AI that provide views into our client’s customer base.

You have:

• 10+ years of experience as a data reliability engineer or related data professional
• 3+ years of experience in modern data ingestion technology tools such as Fivetran for near real time data use.
• 2+ years of experience in Collibra technology tool and data reliability engineering.
• 4+ years of experience and deeper knowledge in data engineering using Python, Pyspark and Databricks
• Hands-on ETL tool Informatica PowerCenter, Informatica Cloud Data integration.
• Experience across multiple RDBMS and managed databases.
• 7+ years of experience strong UNIX scripting.
• Strong SQL, PL/SQL experience.
• Significant experience interfacing with both customers and management across business and IT and track record of collaborating with IT, Business, and vendor teams to provide technical solutions and improvements, delivering end-to-end products/processes on schedule and budget, as per business requirements and SDLC standards.
• Provide Development & Production Support for applications.
• Monitor production jobs, triage issues to appropriate team & resolve any issues in a timely manner.

 

You will:

• Design, implement, and maintain robust data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
• Develop and implement data quality monitoring frameworks to detect anomalies, errors, and inconsistencies in the data pipeline.
• Collaborate with cross-functional teams to understand data requirements and design scalable solutions to meet business needs.
• Implement data governance policies and procedures to ensure compliance with regulatory requirements and industry best practices.
• Optimize data pipeline performance, scalability, and reliability through automation, monitoring, and tuning.
• Troubleshoot and resolve data pipeline issues in a timely manner to minimize disruptions to data workflows.

 

Qualifications:

• Bachelor’s or Master’s degree in computer science, Engineering, or related field
• Proven experience in designing, building, and optimizing data pipelines for analytics
• Excellent problem-solving and troubleshooting skills with a focus on data quality and reliability.