Sr Analyst, Data Engineer

Was wir tun

Bei Kenvue erkennen wir die außergewöhnliche Kraft der täglichen Pflege. Aufbauend auf über einem Jahrhundert Tradition und verwurzelt in der Wissenschaft, sind wir das Haus der ikonischen Marken - darunter NEUTROGENA®, AVEENO®, TYLENOL,® LISTERINE®, JOHNSON'S® und BAND-AID®, die Sie bereits kennen und lieben. Wissenschaft ist unsere Leidenschaft; Fürsorge ist unser Talent.

Wer wir sind

Unser globales Team besteht aus ~ 22.000 brillanten Mitarbeitern mit einer Arbeitsplatzkultur, in der jede Stimme zählt und jeder Beitrag geschätzt wird. Wir sind leidenschaftlich an Erkenntnissen interessiert, Innovation und dem Engagement, unseren Kunden die besten Produkte zu liefern. Mit Fachwissen und Einfühlungsvermögen bedeutet ein Kenvuer zu sein, die Macht zu haben, jeden Tag Millionen von Menschen zu beeinflussen. Wir stellen den Menschen an die erste Stelle, kümmern uns leidenschaftlich, gewinnen Vertrauen in der Wissenschaft und lösen Lösungen mit Mut – und haben brillante Möglichkeiten, die auf Sie warten! Gestalten Sie mit uns unsere Zukunft – und Ihre. Für weitere Informationen, klicken Sie auf hier.

Rollenberichte an:

Standort:

Arbeitsort:

Was Sie tun werden

Position Summary

Provide brief and concise statement explaining the main purpose for the existence of this position.  Provide a brief summary of the role.

• Good understanding of migration and modernization strategies and approaches.

• Helping business migrate and/or build Data, Analytics & AI workloads throughout their Azure journey towards production and expanding the azure infrastructure usage

• Good understanding of Data factory, Databricks, Azure SQL

• Staying current on latest Azure/Cloud innovations in order to conduct experiments, drive product improvement, and act as an Azure subject matter trainer for other engineers

• Development, customize and manage integration tools, databases, warehouses and analytical systems with the use of data related instruments/instances

• Create and run complex queries and automation scripts for operational data processing

• Test the reliability and performance of each part of a system and cooperate with the testing team

• Deploying data models into production environments. This entails providing the model with data stored in a warehouse or coming directly from sources, configuring data attributes, managing computing resources, setting up monitoring tools, etc. 

• Support for setting up tools to view data, generate reports, and create visuals

•  Support to Monitoring the overall performance and stability of the system. Adjust and adapt the automated pipeline as data/models/requirements change.

• As per organizational & project priority responsibilities can be added later

Major Duties & Responsibilities

In order of importance, briefly describe, in sentence form, the essential functions/major responsibilities of this position (principal duties and responsibilities of the position) as it exists today.  Describe the job, not the person in the job.  Each item listed below should be an essential function/major responsibility of the position, not a day-to-day activity.

Typically, job descriptions should contain no more than seven or eight major responsibilities ranked in order of highest percentage of time to least.

Approximate Percentage of Time

Tasks/Duties/Responsibilities

100%

• Support data pipelines from internal and external data sources to support new product launches and drive data quality across data products.

• Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality and performance.

• Support for implementing best practices around systems integration, security, performance and data management.

• Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions.

• Partner with the business, IT, and technical subject matter experts to ensure execution of enterprise-wide data engineering products & platform development.

• Implement DevOps, DataOps and Agile methodologies to improve KPIs like cycle times, consistency, and quality.

• Develop and optimize procedures to “Productionalize” data science models.

100%

Total

Other Duties

Describe important tasks or duties, not mentioned above, that are performed infrequently and are not critical to accomplishing the essential functions of the job.

• Participating in other organization wide activities as part of the duty.

Required Qualification

Consider and identify qualifications potential applicants must possess in order to be considered for the position. Basic Qualifications must be clearly stated, objective and relevant to this particular position.

Required Minimum Education:
Other:

Required Years of Related Experience 2-4 Years

Required Knowledge, Skills and Abilities:

(Include any required computer skills, certifications, licenses, languages, etc.)

Excellent understanding of ETL cycle

• Experience in the design and bu of services using Azure architecture is added advantage

• Azure data engineering certification is good

• Experience in using of Python/ PySpark and/or Scala for data engineering.

• Understanding of data types/ handling of different data models.

• Desirable to have experience with Spark, Kafka, Flask, Python, Neo4J Graph database

• Experience with the Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Synapse, Databricks, deployment of Web Application (Azure) is must

• Good scripting and programming skills.

Travel on the Job:

Indicate whether this position requires travel.

Yes/No

Percentage Traveled: __%

Type of Travel Required:

 Domestic

 International

People Management Experience:

Indicate whether supervisor/people management experience is required.

Yes/No

Required Years of People Management Experience:

Preferred Qualifications

Consider and identify qualifications that are not required to perform the job but would be very helpful to performing the job.

Preferred Minimum Education: Bachelor of Engineering

Other: Azure Data Engineering Certification

Preferred Area of Study:  Data Engineering, Databricks,

Preferred Related Industry Experience (if applicable): Manufacturing & Logistics, IT Service

Preferred Knowledge, Skills and Abilities:

(Include any preferred computer skills, certifications, licenses, languages, etc.)

·        Azure Architect

·        Databricks

·        Azure Data Engineering

·        SQL

·        PLSQL

·        DevOps

Key Working Relationships

Identify the most important working relationships with people inside and outside the company including customers, vendors, associations, etc.  Briefly describe the nature of the contacts.

Internal

JJT, SC Functions, R&D, Commercial business partners; Leadership Teams

External

Vendors, Contractors

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