Combitech söker en Data Engineer i Malmö, Helsingborg eller Göteborg at Combitech in Gothenburg

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Job Description

<h3>Din roll som Data Engineer</h3><p>Vi expanderar snabbt vår verksamhet inom Data Insights, Business Intelligence och Advanced Analytics (Machine Vision, Natural Language Processing, Predictive Maintenance, Optimization och andra AI områden).</p><p>Du kommer att ingå i ett kompetensnätverk där vi jobbar tillsammans i team över hela landet med specialister inom olika kompetensområden. Vi har idag en mix av resurskonsulting, åtagandeverksamhet och produkter/tjänster. Som exempel på vad vi arbetar med kan nämnas skapandet av nya digitala ekosystem inom hållbart resande och transporter, som vi själva använder oss av i vår strävan mot att bli Sveriges mest miljömedvetna konsultföretag.</p><h3>Vem är du?</h3><p>Till teamet, med placering i Södra Sverige (Helsingborg, Malmö och Göteborg) söker vi nu nya konsulter inom Data Engineering. Vi söker främst dig som har kompetens inom Apache Spark och Databricks, men också inom t.ex. Hadoop/Hive eller liknande. Vi ser gärna att du har erfarenhet av Big data och Kubernetes (gärna både i molnet och on-prem). Andra kunskaper som kan vara bra är inom Python och Pandas, samt informationsmodellering och statistiska metoder av olika slag. Har du erfarenhet inom Qlik eller Power BI är det meriterande.</p><p>För att passa in i teamet brinner du för nyskapande, har ett kreativt sinne och strävar efter att lära dig nytt. Konsultrollen ställer även höga krav på social kompetens och affärsmannaskap. Då vi inom detta område jobbar med att utveckla kundernas verksamheter är det viktigt att du har intresse för detta och att du även har förmågan att sätta dig in i kundernas perspektiv. Vårt uppdrag går ut på att skapa värde åt våra kunder.</p><p>Du har relevant högskoleutbildning inom IT. Teknik, matematik och eller statistik. Du är bekväm med både hands-on utveckling och att kunna förstå hur olika komponenter hänger ihop med kundernas behov och levererar värde. Du behöver också ha förståelse för hur man skapar robusta och hållbara lösningar tillsammans med våra arkitekter. Det förutsätter att du har minst 2 års arbetslivserfarenhet inom området.</p><p><strong>Urval sker efter sista ansökningsdatum på grund av sommarsemester. Vi ser fram emot din ansökan!</strong></p><p>Då tjänsten innebär arbete som omfattas av försvarssekretess krävs det att du genomför och godkänns i en säkerhetsprövning med registerkontroll.</p><h3>Kom och gör skillnad</h3><p>Vi tror att man gör ett bättre jobb om man kan fokusera på rätt saker, därför gör vi det lätt att kombinera jobbet med vardagen. Vi satsar på våra medarbetare, de utgör kärnan, hjärnan och hjärtat i vår verksamhet. Dessutom står vi på en stadig grund av högteknologi, forskning och anställningstrygghet med försvars- och säkerhetskoncernen Saab som ägare.</p><p>För oss handlar det om hållbarhet - vi vill bli branschens mest hållbara företag; och för att vara ett hållbart företag i en hållbar framtid behöver vi investera i våra medarbetare. För oss är din återhämtning, dina utvecklingsmöjligheter och din trygghet lika viktigt som företagets framgång - utan våra medarbetare står vi stilla.</p><p><strong>Vill du veta mer om hur det är att arbeta hos oss? Kolla in</strong><strong>våra karriärsidor!</strong></p><p><strong>Kontakt/rekryterande chef: Magnus Brobeck, +46734183465</strong></p>

AI Powered Job Insights

Combitech is on the lookout for a talented Data Engineer to join their team in Malmö, Helsingborg, or Göteborg. This is an exciting opportunity to work at the forefront of data insights and analytics, contributing to meaningful projects that enhance societal benefits.

📍 Location: Malmö, Helsingborg, Göteborg  
💼 Position: Data Engineer  
⏰ Type: Full-time  
📅 Date Posted: 2024-07-02  

Role Summary:  
- The Data Engineer will engage in the rapidly expanding fields of Data Insights, Business Intelligence, and Advanced Analytics.  
- In this role, the individual will collaborate in a nationwide skills network with specialists across various domains, focusing on innovative digital ecosystems aimed at sustainable travel and transport.  

What You'll Do:  
- Work with technologies such as Apache Spark, Databricks, Hadoop, and Kubernetes.  
- Develop big data solutions in both cloud and on-prem environments.  
- Utilize Python and statistical methods for data processing and analysis.  
- Collaborate with architects to create robust and sustainable technical solutions.  

What's Needed:  
- A relevant higher education degree in IT, technology, mathematics, or statistics.  
- At least 2 years of professional experience in Data Engineering and related technologies.  
- Strong understanding of business needs and the ability to translate them into technical solutions.  
- Experience with Qlik or Power BI is a plus.  
- Effective social skills and business acumen are essential, as the role involves developing customer strategies.

Top Interview Questions

  • Q: Can you describe your experience with big data technologies like Apache Spark and Databricks?

    A: I have over three years of experience working with Apache Spark for processing large datasets. In my last role, I implemented a data processing pipeline using Spark on Databricks that reduced processing time by 60%. I leveraged Spark's structured APIs and optimized our queries using DataFrames, resulting in faster real-time analytics.

  • Q: How do you approach data modeling and what tools do you prefer for this task?

    A: I approach data modeling by first understanding the business requirements and how different data entities interact. I typically use tools like ER/Studio or Lucidchart to visualize data models. I also ensure to incorporate normalization and denormalization techniques as necessary to balance performance and usability.

  • Q: Describe a challenging project where you needed to implement predictive analytics. What was your role and what was the outcome?

    A: In a recent project, I led a team to build a predictive maintenance model for manufacturing equipment. My role involved data collection, cleaning, and feature engineering using Python. We employed machine learning algorithms to predict equipment failures. The solution not only reduced downtime by 30% but also saved the company significant costs.

  • Q: How do you ensure the data quality in your ETL processes?

    A: To ensure data quality, I implement validation checks throughout the ETL process. I use automated tests to validate data integrity, identify duplicates, and check for missing values. Additionally, I establish logging mechanisms that notify the team of any data anomalies during the extraction or transformation stages.

  • Q: What strategies do you use for collaborating with team members and stakeholders in a data engineering role?

    A: I prioritize open and continuous communication through regular updates and feedback sessions. I utilize collaboration tools like JIRA for tracking progress and Confluence for documentation. Additionally, I ensure to align with stakeholders by soliciting their input during the design phase to make sure our deliverables meet their expectations.

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