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Regular Data Engineer

  • Inetum
  • Warsaw, Poland
  • PLN 216,000 – PLN 288,000

Company Description

Inetum Polska is part of the global Inetum Group and plays a key role in driving the digital transformation of businesses and public institutions. Operating in cities such as Warsaw, Poznan, Katowice, Lublin, Rzeszow, Lodz the company offers a wide range of IT services. Inetum Polska actively supports employee development by fully funding training, certifications, and participation in technology conferences. Additionally, the company is involved in local social initiatives, such as charitable projects and promoting an active lifestyle. It prides itself on fostering a diverse and inclusive work environment, ensuring equal opportunities for all.

Globally, Inetum operates in 19 countries and employs over 28,000 professionals. The company focuses on four key areas:

  • Consulting (Inetum Consulting): Strategic advisory services that help organizations define and implement innovative solutions.
  • Infrastructure and Application Management (Inetum Technologies): Designing and managing IT systems tailored to clients’ individual needs.
  • Software Implementation (Inetum Solutions): Deploying partner solutions from industry leaders like Microsoft, SAP, Salesforce, and ServiceNow.
  • Custom Software Development (Inetum Software): Creating unique software solutions to meet specific client needs.

With strategic partnerships with major technology giants, including Microsoft, SAP, Salesforce, and ServiceNow, Inetum delivers advanced technological solutions tailored to customer requirements. In 2023, Inetum reported revenues of €2.5 billion, underscoring its strong position in the digital services market.

Inetum distinguishes itself by offering a comprehensive range of benefits that meet the diverse needs of employees, providing flexibility, support and commitment. Here's what makes working at Inetum unique:

Attractive financial benefits:

  • A cafeteria system that allows employees to personalize benefits by choosing from a variety of options.
  • Generous referral bonuses, offering up to PLN6,000 for referring specialists.
  • Additional revenue sharing opportunities for initiating partnerships with new clients.

Professional development and team support:

  • Ongoing guidance from a dedicated Team Manager for each employee.
  • Tailored technical mentoring from an assigned technical leader, depending on individual expertise and project needs.

Community and Well-Being:

  • Dedicated team-building budget for online and on-site team events.
  • Opportunities to participate in charitable initiatives and local sports programs.
  • A supportive and inclusive work culture with an emphasis on diversity and mutual respect.

Job Description

Join an exciting Data Engineering project in the aviation industry, where modern cloud and Big Data technologies are used to support predictive maintenance solutions for aircraft engines.

The project focuses on developing and enhancing a scalable data platform that processes large volumes of operational and technical data. By transforming complex datasets into reliable and accessible information, the platform enables advanced analytics related to engine performance, maintenance needs, and operational efficiency.

As a Data Engineer, you will join an established engineering team and work with technologies such as Microsoft Azure, Databricks, Apache Spark, Python, and SQL. You will be responsible for building and optimizing data pipelines, processing large-scale datasets, and ensuring high quality and availability of data for analytical use cases.

This is a great opportunity for someone who enjoys solving complex data challenges and wants to work on a project where modern Data Engineering has a direct impact on the reliability and maintenance of advanced aviation systems.

Main Tasks

  • Design, develop, and maintain scalable data pipelines using Azure Databricks, Apache Spark, Python, and SQL
  • Process and transform large volumes of operational and technical data supporting predictive maintenance and analytical use cases
  • Develop and optimize ETL/ELT processes for efficient data ingestion, transformation, and storage
  • Design and implement CI/CD processes for Databricks applications using Azure tooling, including Terraform and Databricks Asset Bundles (DABs)
  • Work with Azure data processing and storage services to build reliable and scalable data solutions
  • Optimize Spark workloads and improve overall data processing performance
  • Implement data validation and quality checks to ensure consistency, accuracy, and reliability of datasets
  • Collaborate with Data Engineers and project stakeholders to translate business and data requirements into technical solutions
  • Contribute to the continuous development, maintenance, and improvement of the existing data platform
  • Troubleshoot data processing issues and improve the stability and performance of data pipelines
  • Prepare and maintain technical documentation for implemented solutions and data workflows

Qualifications

Must-have requirements

  • Commercial experience in Data Engineering
  • Hands-on experience with Databricks
  • Experience in implementing CI/CD for Databricks applications
  • Practical experience with Microsoft Azure data processing and storage services
  • Strong experience with Apache Spark
  • Good knowledge of SQL
  • Hands-on development experience with Python
  • Good understanding of Big Data processing concepts, standards, and tools
  • Experience working with large-scale data processing pipelines and ETL/ELT processes

Nice to have

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, or a related technical field

Additional Information

We hereby inform you that Inetum Polska sp. z o.o. has implemented an internal reporting (whistleblowing) procedure. The content of the procedure and the possibility to submit an internal report are available at:

https://inetum.whispli.com/speakup?locale=pl

Skills

  • SQL
  • Python
  • ETL
  • Data Modeling
  • Apache Spark
  • Airflow
  • Cloud Data Platforms

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