Senior Data Engineer

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Date: May 3, 2023

Location: Pune, IN

Company: Bekaert NV

 

Be part of something bigger!

 

As the world and the way people live is changing, at Bekaert we believe it’s our responsibility to contribute to finding new solutions for the future. Our ambition is to be the leading partner for shaping the way we live and move. And to always do this the Bekaert Way – safe, smart, and sustainable.

With a heritage of more than 140 years, we continue to strengthen our core competencies that have made Bekaert a global market and technology leader in material science of steel wire transformation and coating technologies. Today, we also apply our expertise beyond steel to create new solutions with innovative materials and services for markets including new mobility, low-carbon construction, and green energy.

As a dynamic and growing company with over 27,000 employees worldwide, 75 nationalities, a retention rate above 90% and almost € 7 billion in combined revenue in 2022, we're looking for someone like you to join our team!

 

Why join us?

  • Personal Growth – Let us help you unlock your full potential
  • Pioneering – Join us to challenge the impossible
  • Creativity - Discover possibilities beyond steel
  • Purpose – Drive progress for our planet and people
  • Diversity – Together, we create change

 

 

 

 

 

 

 

JOB DESCRIPTION

 

Date :  

 

Department :

 

I. IDENTIFICATION                                                                               

 

Job Name :  Data Engineer

 

Job Holder :                                                                                    

 

Superior Position :

 

Name Superior :                                                                              

 

II. PURPOSE OF THE JOB  

 

The data engineer will play a pivotal role in building and operationalizing the minimally inclusive data necessary for the enterprise data and analytics initiatives following industry standard practices and tools. The bulk of the data engineer’s work will be in building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for key data and analytics consumers like business/data analysts, data scientists or any persona that needs curated data for data and analytics use cases across the enterprise.

 

Data engineers also need to guarantee compliance with data governance and data security requirements while creating, improving and operationalizing these integrated and reusable data pipelines. This would enable faster data access, integrated data reuse and vastly improved time-to-solution for data and analytics initiatives. The data engineer will be measured on their ability to integrate analytics and (or) data science results with business processes.

 

The data engineer will be the key interface in operationalizing data and analytics on behalf of the business unit(s) and organizational outcomes. This role will require both creative and collaborative working with IT and the wider business. It will involve evangelizing effective data management practices and promoting better understanding of data and analytics. The data engineer will also be tasked with working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal analytics and data science solutions.

 

Additionally, data engineers will also be expected to collaborate with data scientists, data analysts and other data consumers and work on the models and algorithms developed by them in order to optimize them for data quality, security and governance and put them into production leading to potentially large productivity gains.

 

 

Key responsibilities

  • Build data pipelines: Managed data pipelines consist of a series of stages through which data flows (for example, from data sources or endpoints of acquisition to integration to consumption for specific use cases). These data pipelines must be created, maintained and optimized as workloads move from development to production for specific use cases. Architecting, creating and maintaining data pipelines will be the primary responsibility of the data engineer.
  • Drive Automation through effective metadata management: The data engineer will be responsible for using innovative and modern tools, techniques and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity. The data engineer will also need to assist with renovating the data management infrastructure to drive automation in data integration and management.

This will include (but is not be limited to):

    • Learning and using modern data preparation, integration and AI-enabled metadata management tools and techniques.
    • Tracking data consumption patterns.
    • Performing intelligent sampling and caching.
    • Monitoring schema changes.
    • Recommending — or sometimes even automating — existing and future integration flows.
  • Collaborate across departments: The data engineer will need strong collaboration skills in order to work with varied stakeholders within the organization. In particular, the data engineer will work in close relationship with data science teams and with business (data) analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
  • Educate and train: The data engineer should be curious and knowledgeable about new data initiatives and how to address them. This includes applying their data and/or domain understanding in addressing new data requirements. They will also be responsible for proposing appropriate (and innovative) data ingestion, preparation, integration and operationalization techniques in optimally addressing these data requirements. The data engineer will be required to train counterparts such as [data scientists, data analysts, LOB users or any data consumers] in these data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
  • Participate in ensuring compliance and governance during data use: It will be the responsibility of the data engineer to ensure that the data users and consumers use the data provisioned to them responsibly through data governance and compliance initiatives. Data engineers should work with data governance teams (and information stewards within these teams) and participate in vetting and promoting content created in the business and by data scientists to the curated data catalog for governed reuse.
  • Become a data and analytics evangelist: The data engineer will be considered a blend of data and analytics “evangelist,” “data guru” and “fixer.” This role will promote the available data and analytics capabilities and expertise to business unit leaders and educate them in leveraging these capabilities in achieving their business goals.

 

 

Skills & Competencies

Technical and Business Knowledge/Skills

  • Foundational knowledge of Data Management practices.
  • Strong experience with various Data Management architectures like Data Warehouse, Data Lake and the supporting processes like Data Integration, Governance, Metadata Management
  • Strong ability to build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata, and workload management.
  • Strong experience with working in Azure environment using Azure Data Factory, Azure data lake, Synapse Analytics.
  • Strong experience with popular database programming languages including SQL, PL/SQL, others for relational databases
  • Some experience with Python to do data Engineering activities.
  • Basic experience in working with data governance/data quality and data security teams and specifically information stewards and privacy and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification.
  • Basic experience in working with DevOps capabilities like version control, automated builds, testing and release management capabilities using Azure DevOps.
  • Basic experience working with popular data discovery, analytics and BI software tools like Power BI or Tableau.
  • Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows.

Interpersonal skills & Characteristics

  • Strong experience supporting and working with cross-functional teams in a dynamic business environment.
  • Required to be highly creative and collaborative. An ideal candidate would be expected to collaborate with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly. The successful candidate will also be required to have regular discussions with data consumers on optimally refining the data pipelines developed in nonproduction environments and deploying them in production.
  • Required to have the accessibility and ability to interface with, and gain the respect of, stakeholders at all levels and roles within the company.
  • Is a confident, energetic self-starter, with strong interpersonal skills.
  • Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.

Education:

A bachelor's or master's degree in computer science, or equivalent through work experience.

Experience Required: 

  • At least Two years or more of work experience in data management disciplines including data integration using Azure Data Factory, Azure data lake, Synapse Analytics and/or other areas directly relevant to data engineering responsibilities and tasks.
  • At least 1 year or more of work experience in reporting using Power BI or other areas directly relevant to reporting responsibilities and tasks.
  • At least 1 year or more of work experience in Python for data Engineering activities.
  • At least two years of experience working in cross-functional teams and collaborating with business stakeholders to understand the requirements.
  • Knowledge of the Agile process and experience working in an Agile environment
  • Good to have exposure to SAS Viya

 

 

Will you dare to take the next step?

 

Join us to unlock your full potential AND have a true impact in pushing the boundaries of what is possible.

We're looking for individuals who are not afraid to take risks and explore new ideas. If you are passionate about personal growth and bringing your authentic self to work, we want you on our team!

At Bekaert, we celebrate diversity and are committed to creating an inclusive work environment. We do not discriminate based on race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.

To learn more about us and our exciting career opportunities, visit Bekaert Careers 

 

Our Digital Advanced Solutions (ADS) team is a mighty group of technologists from across the globe who continuously push the envelope in Digital, Cyber resilience, data science, intelligent automation, Cloud solutions and New (Agile) ways of working. Want to learn more about our digital opportunities?

 


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