Data Engineer Ii - Tijuana, México - Thermo Fisher Scientific

Thermo Fisher Scientific

Empresa verificada

Tijuana, México

hace 1 semana

Publicado por:

Rodrigo Fernández

Reclutador de talento para beBee

Descripción

When you are part of the team at Thermo Fisher Scientific, you'll do important work, like helping customers in finding cures for cancer, protecting the environment, or making sure our food is safe.

Your work will have a real-world impact, and you'll be supported in achieving your career goals.

Location/Division Specific Information

Data Engineer II plays 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.

How will you make an impact?

Being part of an organization that provides data solutions for all businesses across Thermo Fisher Scientific, you will be instrumental in helping our business partners and customers with their data and analytics needs.

What will you do?

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, redesigning infrastructure for greater scalability, etc.
Work with collaborators, including the Executive, Product, Data, and Design teams to assist with datarelated 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 oncall schedule to address critical operational incidents and business requests.

How will you get here?

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.

Experience & Skills:

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, userdefined 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.

Knowledge, Skills, Abilities

Experience with agile development methodologies by following DevOps, Data Ops and Dev Sec Ops practices.
Manage life cycle of ETL Pipelines and other cloud platform tools, including GitHub, Jenkins, Terraform, Jira, and Confluence.
Functional knowledge in the areas of Sales and distribution, Material Management, Finance and Production Planning is preferred.
Excellent written, verbal, and interpersonal and stakeholder communication skills.
Ability to analyze trends associated with huge datasets.

Benefits:

We offer competitive remuneration, annual incentive plan bonus scheme,and a range of employee benefits Thermo Fisher Scientific offers employment with an innovative, forward-thinking organization, and outstanding career and development prospects.

We offer an exciting company culture that stands for integrity, intensity, involvement, and innovation.

Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other