Data Engineer II

hace 4 semanas

Tijuana, Baja California, México Thermo Fisher Scientific A tiempo completo

At Thermo Fisher Scientific, you'll be part of a team that makes a real-world impact. As a Data Engineer II, you'll play a key role in Enterprise Data Platform (EDP) Operations organization, providing business continuity for critical business processes, IT systems, and IT solutions through project implementations, improvements, documentation, and operational support.

Key Responsibilities:

  • Own and deliver enhancements associated with Data platform solutions.
  • Maintains and enhances scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
  • Enhance/Support solutions using Pyspark/EMR, SQL and databases, AWS Athena, S3, Redshift, AWS API Gateway, Lambda, Glue, and other Data Engineering technologies.
  • Write complex queries and edit them as needed for implementing ETL/Data solutions.
  • Implement solutions using AWS and other cloud platform tools, including GitHub, Jenkins, Terraform, Jira, and Confluence.
  • Follow agile development methodologies to deliver solutions and product features by following DevOps, Data Ops and Dev Sec Ops practices.
  • Propose data load optimizations and continuously implement them to improve their performance.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Work with collaborators, including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Keep the data separated and secure across through multiple data centers and AWS regions.
  • Be available and participate in on-call schedule to address critical operational incidents and business requests.

Requirements:

  • Bachelor's degree in computer science required.
  • Having certifications like AWS Certified Data Analytics, CCA Spark and Hadoop Developer or CCP Data Engineer is preferred.
  • 3+ years of overall IT Experience with at least 1+ years of experience in Data Lake, Data Analytics & Business Intelligence Solutions as AWS Data Engineer.
  • Full life cycle project implementation experience in AWS using Pyspark/EMR, Athena, S3, Redshift, AWS API Gateway, Lambda, Glue, and other managed services.
  • Strong experience in building ETL data pipelines using Pyspark on EMR framework.
  • Hands on experience in using S3, AWS Glue jobs, S3 Copy, Lambda and API Gateway.
  • Working SQL experience to troubleshoot SQL code. Redshift knowledge is an added advantage.
  • Strong experience in DevOps and CI/CD using Git and Jenkins, experience in cloud native scripting such as CloudFormation and ARM templates.
  • Experience working with Python and Python ML libraries for data analysis, wrangling, and insights generation.
  • Experience using Jira for task prioritization and Confluence and other tools for documentation.
  • Strong analytical experience with databases in writing complex queries, query optimization, debugging, user-defined functions, views, indexes, etc.
  • Experience with source control systems such as Git, Bitbucket, and Jenkins build and continuous integration tools.
  • Exposure to Kafka, Redshift, and Sage Maker would be an added advantage.
  • Exposure to data visualization tools like Power BI, Tableau, etc.

What We Offer:

  • Competitive remuneration.
  • Annual incentive plan bonus scheme.
  • A range of employee benefits.
  • Employment with an innovative, forward-thinking organization.
  • Outstanding career and development prospects.
  • An exciting company culture that stands for integrity, intensity, involvement, and innovation.

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