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Senior Data Engineer

External
intrum logoIntrum · Riga, Latvia
Full-timeOn-siteToday
ApacheAWSAzureBashCI/CDdbt
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Requirements

  • Apache Kafka.
  • Basic Linux knowledge, including bash.
  • Databricks data engineering or Spark certificates..
  • Knowledge of DBT.
  • Bachelor's or Master's degree in Computer Science, Software
  • Engineering, or related field is an advantage

Benefits

At Intrum we offer not only a challenging and rewarding career but also:An exciting and developing position in an international company with growth ambitionsHighly motivated and skilled co-workers globallyBeing part of a supportive culture where effort countsWe facilitate your learning through different learning arenasAbout Intrum:Intrum is the industry-leading provider of credit management services across 20 markets in Europe. By helping companies to get paid and support people with their late payments, Intrum leads the way to a sound economy and plays a critical role in society at large.Intrum has circa 9,000 dedicated professionals who serve around 70,000 companies across Europe.How to apply : If you are interested in this position and believe you have the right qualifications, please send your English CV and a cover letter via the "apply button"**Please note that as a multinational company, our Global Talent Acquisition Partner is based in Spain. You might receive a call with a Spanish phone number.**At Intrum we strive to create a diverse and inclusive workplace. We encourage applicants from all backgrounds to apply.Do you feel that you might be the right person? Great! Apply now. Looking forward to hearing from you!

Additional Information

At Intrum, you will grow by making a difference. You will do it in a highly international environment and in a supportive culture where effort counts. Are you our new Senior Data Engineer? What will you do: Implement data pipelines from source systems to analytics and reporting layers. Lead optimizations to improve workloads performance, reliability, and cost efficiency, performance tuning, scalability, and reliability of data platforms. Maintain data models, schemas, and metadata documentation. Develop and maintain deployment pipelines for schemas, ETL/ELT processes to support CI/CD and DevOps practices. Contribute to implementation of advanced data quality, observability, and lineage frameworks. Lead code reviews, documentation, and continuous improvement initiatives. Ensure adherence to global data security, privacy, and regulatory requirements. Clearly communicate about development progress, risks, obstacles and propose solutions how to mitigate and resolve them. Work with other team members to ensure usage of development best practices. Support other team members in case of questions related to Data Engineering area. Participate in technical design development. Support data consumers by answering their questions. Perform production support activities. What we´re looking for: Experience in building data pipelines/transformations. Experience with Azure stack (ADLS, Azure Blob, Delta Lakehouse). Experience with Databricks (jobs, declarative automation bundles). Experience with PySpark and Python in general. Experience with building data processing pipelines (ETL/ELT). Experience with SQL, including understanding of performance aspects. Hands-on experience with cloud platforms (e.g. Azure - preferred, AWS, GCP), Solid understanding of data platform design principles, scalability, performance, and costs aspects. Familiarity with CI/CD pipelines (Azure DevOps - preferred). Solid understanding of distributed computing, Spark optimization, and performance tuning. Good understanding of SDLC. Ability to lead technical initiatives in Data Engineering area and mentor team members. Strong analytical, problem-solving and communication skills. Fluent English.

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