ジョブファンクション: インフォメーション システム（IS)
所在地: New York, NY
国/地域: United States
L'Oreal USA, Hudson Yards NYC
Digital IT Director, E-Commerce Lead Data Engineer,
We are looking for a savvy data engineering professional to join a pioneering team of architects, engineers and analytics experts. The role will be responsible for building data solutions including architecture, pipelines and visualizations and work hand in hand with business teams on data driven decisions. The role will operate across multiple e-commerce channels and divisions for L’Oreal USA, keeping the consumer at the forefront while driving enhanced experiences and profitable E-Commerce growth. They must be self-driven and comfortable working in a product model.
- Create and maintain optimal data models and data pipeline architecture
- Assemble large, complex data sets via a new and central data platform ecosystem that meet functional / non-functional business requirements.
- Build analytics and business intelligence solutions to provide actionable insights into e-commerce pillars, operational efficiency and other key business performance metrics.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using API, ETL, SQL and cloud ‘big data’ technologies.
- 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 and cloud regions.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with business teams and data experts to strive for greater functionality in our data systems.
Knowledge, Skills, and Abilities
We are an Equal Opportunity Employer and take pride in a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or disability, or any other legally protected status. If you require a reasonable accommodation to complete an application for a recognized disability under applicable law, please email USApplicationAccommodation@support.lorealusa.com. Please note this email will only respond to specific requests for assistance completing the application as a request for accommodation for a disability. All others will not be considered.
- 2+ years of prior experience in building solutions for Digital & E-Commerce teams
- 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.
- Experience using the many of the following tools:
- Experience with big data tools and skills: Python, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, such as MySQL, Postgres and Cassandra.
- Experience with public cloud services such as AWS EMR, RDS, Redshift, Google BigQuery
- Strong experience with visualizing insights via traditional BI tools such as PowerBI, Tableau, Domo etc.
- Experience with data pipeline and workflow management tools: Airflow, Informatica BDM etc.
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- 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.
- Some experience in working with APIs and stream processing
- Strong communication and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.