Data Engineer @ Capgemini Polska Sp. z o.o. (práce v Polsku)

Data Engineer @ Capgemini Polska Sp. z o.o.

Polsko

YOUR PROFILE

• 3+ years of experience in a Data Engineer role 
• Experience with stream-processing systems, such as Apache Spark and/or Kafka Streaming, Storm, etc. 
• Experience with programming and scripting languages: Python, Scala 
• Experience working with relational databases and data warehouses, including Postgres, Microsoft SQL Server, Oracle, GCP BigQuery, etc. 
• Experience with Big Data tools: Hadoop, Spark, Hive, HBase, etc. 
• Experience with NoSQL data repositories, Elastic Search ideally 
• Experience building and optimizing big data pipelines, architectures, and data sets 

Data Engineer (multilocation)

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

WHAT YOU’LL LOVE ABOUT WORKING HERE

• Well-being culture: medical care with Medicover, private life insurance, and Multisport card. But we went one step further by creating our own Capgemini Helpline offering therapeutical support if needed and the educational podcast "Lets talk about wellbeing" which you can listen to on Spotify. 
• Access to over 70 training tracks with certification opportunities (e.g., GenAI, Excel, Business Analysis, Project Management) on our NEXT platform. Dive into a world of knowledge with free access to Education First languages platform, Pluralsight, TED Talks, Coursera and Udemy Business materials and trainings. 
• Continuous feedback and ongoing performance discussions thanks to our performance management tool GetSuccess supported by a transparent performance management policy. 
• Enjoy hybrid working model that fits your life - after completing onboarding, connect work from a modern office with ergonomic work from home, thanks to home office package (including laptop, monitor, and chair). Ask your recruiter about the details. 

GET TO KNOW US

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. We evaluate individuals based on qualifications and performance, not personal characteristics, striving to create a workplace where everyone can succeed and feel valued.

Do you want to get to know us better? Check our Instagram — @capgeminipl or visit our Facebook profile — Capgemini Polska. You can also find us on TikTok! — @capgeminipl.

ABOUT CAPGEMINI

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members globally in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. 
 

Apply now!

Ref. code:  99014 Posted on:  31 Oct 2024 Experience Level:  Experienced Professionals Contract Type:  Fixed Term Contract Location: 

Katowice, PL Lublin, PL Opole, PL Wrocław, PL Gdańsk, PL Kraków, PL Poznań, PL Warszawa, PL

Brand:  Capgemini Engineering Professional Community:  Software Engineering

,[We are looking for a savvy 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 software developers, database architects, data analysts, and data scientists 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 about the prospect of optimizing or even re-designing our companys data architecture to support our net generation of products and data initiatives., Create and maintain optimal data pipeline architecture , Assemble large, complete data sets that meet functional / non-functional business requirements. Identified, designed, and implemented internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, performance, 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 customer acquisition, revenue management, operational efficiencies, 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 and regions. , Create data tools for analytics and data scientist team members that assist them in building and optimizing our offerings. , Work with data and analytics experts to strive for greater functionality in our data systems. ] Requirements: R, SQL, Big Data, Apache Spark, Kafka, Storm, Scripting language, Scala, Relational database, Data warehouses, PostgreSQL, Microsoft SQL Server, Oracle, GCP, BigQuery, Hadoop, Spark, Hive, HBase, NoSQL, Data pipelines, Excel, Project management, Cloud Additionally: Sport Subscription, Private healthcare, Home office, Certificates, Pluralsight, Life insurance, Udemy for business, Modern office.

Kategorie

data

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