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Thermo Fisher Scientific

Lead Data Engineer

Thermo Fisher Scientific | Waltham, MA, US, 02254

Salary Range:$83,000 – $107,000 Salary range estimated by Zippia

Posted a day ago


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Description

Job Description

DUTIES:

Build, enhance and support data ingestion pipelines, data lakes, and data warehouse across a variety of infrastructure (both on-prim and cloud).

Collaborate with infrastructure and IT team to design, create, and maintain optimal data pipeline architecture and data structures for Enterprise Data Platform.

Collaborate on design, development, testing, and automation phases of solution implementation.

Work with product team to define release timelines and socialize them with the business needs.

Assemble and consolidate complete data sets from business and reporting systems such as Business Objects, Cognos/EDW/CDW, E1, and Salesforce.

Automate manual data acquisition processes and optimize data delivery.

Develop customized SQL queries for database solutions and business ad hoc requests.

Conduct data integration, data integrity to improve data fidelity in for real time analytics.

Work with business stakeholders to understand their data analytics and machine learning needs and optimize datasets, pipelines, and solutions for generating business KPI metrics.

Collaborate on design, development, testing, and automation phases of solution implementation.

Travel: Up to 10% domestic and international travel required. Can work remotely

REQUIREMENTS:

MINIMUM Education Requirement: Master's degree, or foreign degree equivalent, in Computer Science, Information Systems, Computer Engineering, or related field of study.

MINIMUM Experience Requirement: 2 years of experience in data integration or related experience.

Alternative Education and Experience Requirement: Bachelor's degree or foreign degree equivalent in Computer Science, Information Systems, Computer Engineering, or related field of study plus 5 years of experience in data integration or related experience. Required knowledge or experience with:
• SQL Queries (various joins, correlated subqueries, recursive queries);
• Python development and Python libraries;
• ERP (Oracle, JDE, SAP);
• Datawarehouse, cloud source systems (Workday, Sales Force);
• Scala, SQL programming and Amazon Web Services (AWS); and
• Cloud Services: S3, Lambda, EMR, Redshift and Data Bricks (Spark).

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