Data Engineer at Redeploy in Västra Götaland County, Sweden

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Job Description

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 Redeploy is a powerhouse of cloud-native specialists, combining Azure, AWS, data, and AI expertise. Our certified strategists, architects, developers, and engineers craft and implement cloud-native solutions, from the initial vision and strategy to developing, migrating, and managing cloud environments. Our teams across Sweden, Germany, Lithuania, and Poland assure enterprises of a comprehensive and integrated approach to their journey, focusing on reliable, secure, and efficient cloud-native solutions. For more information, go to redeploy.com/about
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  About Redeploy Insight
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 At Redeploy Insight, we specialize in building modern cloud data platforms to serve clients across the Nordics to enable enterprise-scale analytical capabilities. Our core focus lies in delivering cutting-edge solutions, including consulting expertise, managed services, and SaaS Data &amp; AI platforms. We take pride in our strategic partnerships with industry leaders such as Microsoft &amp; Databricks, positioning ourselves at the forefront of technological innovation.
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 Redeploy Insight has successfully delivered large-scale and innovative data platforms to Electrolux, Coop, Folksam, PostNord, and Handelsbanken to name a few. Our dedicated team is passionate about enabling enterprise-scale analytical capabilities, empowering our clients to gain profound insights and make informed, impactful decisions.
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 The demand for cloud based analytical platforms is constantly growing and we are now looking for a Data Engineer to join our growing team in Stockholm or Gothenburg. You will work in a fast-paced environment where you will collaborate with some of the most brilliant minds in the field and contribute to the evolution of our platforms with your expertise Data Engineering.
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  About The Role
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 As a Data Engineer in our backend team, you will help to ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable, given a specific set of business requirements and constraints. You will deal with unanticipated issues swiftly and minimize data loss. You will also design, implement, monitor, and optimize data platforms to meet the data pipeline needs.
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 In this role we see that you have knowledge of data processing languages, such as SQL, or Python, and an understanding of parallel processing and data architecture patterns.
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  To be considered for the role, we see that you come with the following experiences and skills:
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   University degree in Computer Science, Information Technology or Engineering.
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   1-3 years of experience as Data Engineer or similar role
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   Familiar with Microsoft Azure Data lake, Databricks, SQL database and data warehouse solutions.
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   Experience in designing, implementing, and supporting enterprise-scale ETL / ELT pipelines.
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   Ability to integrate data from a variety of sources using integration and orchestration tools (e.g. Azure Data Factory).
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   Fluency in Swedish and English with good communication skills.
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  You are
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   A Social team-player with drive and positive attitude
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   Analytical, communicative, and driven
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   A flexible person with &ldquo;Can-do mentality&rdquo;
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   Experienced in planning and executing in your projects
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  You would like to work with us if you
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   Want to work with the latest technology and projects within in Analytics and AI
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   Are motivated by customer challenges
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   Like to work in teams and are humble
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   Want to be in a workplace where your thoughts are valued, and your ideas make an impact
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  How To Apply
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 If you're ready to launch your career and make a meaningful impact on organizations through your passion for Data Engineering, then don&rsquo;t hesitate to send in your application by hitting the apply button.
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 We look forward to hearing from you!
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   Note:
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  To be
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 eligible for the role you need to be based in Stockholm or Gothenburg, or have plans to relocate to either of the locations.
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AI Powered Job Insights

They are seeking a Data Engineer to join their dynamic team at Redeploy Insight in Sweden. This is an exciting opportunity for professionals interested in cloud-based analytical platforms, as they focus on providing innovative data solutions for leading Nordic companies. 

📍 Location: Västra Götaland County, Sweden  
💼 Position: Data Engineer  
⏰ Type: Full-time  
📅 Date Posted: 2024-07-05  

Role Summary:  
- The Data Engineer will contribute to creating and optimizing high-performing data pipelines and stores.  
- They will ensure reliable data handling and swift issue resolution.  

What You'll Do:  
- Design, implement, monitor, and optimize data platforms to meet pipeline needs.  
- Collaborate with a talented team to evolve data platforms and manage enterprise-scale ETL/ELT pipelines.  

What's Needed:  
- A university degree in Computer Science, Information Technology, or Engineering.  
- 1-3 years of experience in a Data Engineer or similar role.  
- Familiarity with Azure Data Lake, Databricks, SQL databases, and data warehouse solutions.  
- Skills in integrating data using orchestration tools like Azure Data Factory.  
- Fluency in Swedish and English, with strong communication abilities.  

Ideal Candidate:  
- A social team player with a positive attitude and analytical mindset.  
- A flexible individual with a “can-do” mentality, capable of project planning and execution.  

They welcome those who are passionate about leveraging the latest technology in Analytics and AI, motivated by customer challenges, and prefer teamwork in an environment where ideas are valued.

Top Interview Questions

  • Q: Can you describe your experience with designing and implementing ETL/ELT pipelines?

    A: I have designed and implemented ETL pipelines using Azure Data Factory, where I streamlined data extraction from various sources, transformed it using data flows for cleansing and aggregation, and loaded it into an Azure SQL Database. For example, I successfully integrated data from multiple business systems, which resulted in a 40% improvement in reporting accuracy and a reduction in processing time.

  • Q: How do you ensure data quality and reliability in the data pipelines you build?

    A: To ensure data quality, I implement validation checks at various stages of the ETL process. This includes using anomaly detection to identify data discrepancies and creating alerts for data failures. I also regularly review logs and perform data profiling to maintain consistency and reliability. In my previous role, these practices helped decrease data quality issues by over 30%.

  • Q: Can you provide an example of a challenge you faced while working with cloud data platforms and how you resolved it?

    A: In one project, I encountered a bottleneck due to inefficient data loading in the Azure Data Lake. To address this, I assessed the data ingestion process and optimized the partitioning strategy. I implemented parallel processing during loading and adjusted the configuration of the data flows. This resulted in a significant improvement in performance, reducing loading times by around 50%.

  • Q: What tools and languages do you find most effective for data processing and why?

    A: I primarily use SQL for querying and data manipulation due to its efficiency in handling structured data. For larger datasets or complex processing tasks, I leverage Python with libraries like Pandas for data transformation and Azure Data Factory for orchestration. Combining these tools allows me to balance performance with flexibility in managing data workflows.

  • Q: How do you prioritize and manage your tasks when working on multiple data engineering projects simultaneously?

    A: I prioritize my tasks by assessing project deadlines and the business impact of each assignment. I utilize project management tools like Jira to keep track of progress and set reminders for key milestones. Regular communication with stakeholders is also critical to understand shifting priorities. This approach allows me to stay organized and ensure timely delivery across all projects while maintaining quality.

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