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Data Engineer

New York City, NY | Full Time
6 Days Ago

Job Description

About Maesa

Maesa is the world's largest independent beauty incubator, housing numerous, fast growing "it" brands within all categories of beauty. We are a high growth global company in the middle of the transition from founder lead to private equity owned. With an incubation flywheel ideating on new global brand launches, Maesa pushes creative and technical boundaries to deliver exceptional performance and establish global staying power. Maesa has a keen focus on marketing and white space analysis, which guides its thinking on marketing existing brands as well as development of new brands through its extremely unique structure. We are vertically integrated globally with inhouse marketing, branding, product development/formulation, packaging design/engineering and regulatory. With a focus on modernity and sustainability, we design innovative solutions and make proactive choices to achieve environmental neutrality and consumer wellness. Maesa has mastered "commercializing creativity," making itself a leader in the fundamental revolutionary change in the beauty industry. Headquartered in New York and Paris, with additional offices in Los Angeles, Vienna, Dubai, Hong Kong, and Dongguan, Maesa employs about 400 team members worldwide.

We are looking for a Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our business units on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives

Responsibilities:

  • Create and maintain optimal data pipeline architecture, 
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies. 
  • Build analytics tools that utilize the data pipeline to provide actionable insights into financial and operational efficiency and other key business performance metrics. 
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. 
  • Keep our data separated and secure across national boundaries through multiple data centers. 
  • Create data tools for analytics and team members that assist them in building and optimizing our product into an innovative industry leader. 
  • Work with data and analytics experts to strive for greater functionality in our data systems. 

Qualifications:

  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. 
  • Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. 
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. 
  • Strong analytic skills related to working with unstructured datasets. 
  • Build processes supporting data transformation, data structures, metadata, dependency, and workload management. 
  • A successful history of manipulating, processing and extracting value from large disconnected datasets. 
  • Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. 
  • Strong project management and organizational skills. 
  • Experience supporting and working with cross-functional teams in a dynamic environment. 
  • We are looking for a candidate with 5 years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: 
  • Experience with big data  
  • Experience with relational SQL and NoSQL databases 
  • Experience with data pipeline and workflow management 
  • Experience with cloud services 
  • Experience with object-oriented/object function scripting languages: Python, Java, C , Scala, etc.

Any offer of employment is contingent on providing proof of COVID-19 vaccination prior to your start date, subject to approved medical and/or religious exemptions, in accordance with applicable law.

#LI-Hybrid

Company Overview

  • Website maesa.com
  • Headquarters NEW YORK, NY
  • Size 200 - 500
  • Founded 1997
  • Type Private
  • CEO SUZAN TILLOSTON
  • Revenue $200M - $500M
  • Industry Business Services
  • About maesa
  • Maesa designs and manufactures private labels for drug and specialty retailers.

Skills for Data Engineer

The job skills required for Data Engineer include SQL, Python, Computer science, Analysis, Insight,and data infrastructure etc. Having related job skills and expertise will give you an advantage when applying to be a Data Engineer. That makes you unique and can impact how much salary you can get paid. Below are job openings related to skills required by Data Engineer. Select any job title you are interested in and start to search job requirements.

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Career Path for Data Engineer

The following is the career advancement route for Data Engineer positions, which can be used as a reference in future career path planning. As a Data Engineer, it can be promoted into senior positions as a Database Engineer IV that are expected to handle more key tasks, people in this role will get a higher salary paid than an ordinary Data Engineer. You can explore the career advancement for a Data Engineer below and select your interested title to get hiring information.

How to Become a Data Engineer

If you are interested in becoming a Data Engineer, you need to understand the job requirements and the detailed related responsibilities. Of course, a good educational background and an applicable major will also help in job hunting. Below are some tips on how to become a Data Engineer for your reference.

Step 1 Understand the job description and responsibilities of a Data Engineer

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