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Senior Data Engineer (m/w/d) für Teamaufbau im Consulting
  • Job type: Permanent
  • Location: Munich, Bayern
  • Salary: €80000 - €100000 per annum
  • Description Im Bereich Data Warehousing arbeitet mein Kundenunternehmen aktuell noch mit einer Tochterfirma aus der Schweiz zusammen, möchte jetzt jedoch das Know-How nach München holen und sucht dafür eine
Senior Data Engineer (m/w/d) Hadoop mit Team Lead Option
  • Job type: Permanent
  • Location: Munich, Bayern
  • Salary: €80000 - €100000 per annum
  • Description Weltweites Experten Know-how, über 100.000 IT-Mitarbeiter und mehr als 40 Jahre Erfahrung - Wenn dir hervorragende Business-Kontakte, ein umfassendes Budget für Innovation und ein sicherer

A data engineer manages and creates a company’s data tools and infrastructure, and obtains the desired results from a huge amount of often complex data. The definition of data engineering role often varies, and the role has crossover with that of a data scientist. A data engineer is tasked with transforming data into a specific format that can be easily analyzed. They do this by developing, testing, and maintaining infrastructures for required data generation. They closely work with data scientists and provide architectural solutions for data scientists that help them to perform their tasks.   

Job Specification, Salary, Outlook
Data engineers are generally responsible for the maintenance, cleaning, manipulation and improvement of data in the analytics and operations databases of the business. They work with data analytics teams, data warehouse engineers, data scientists and software engineers, in order to understand database requirements and troubleshoot any issues. 

A data engineer should be an expert in SQL development; this is required for analysis activities, data flow and database design. A data engineer plays a vital role in the development as well as deployment of big data platforms for data processing and advanced analytics. They build and define the data pipelines that enable data-led, faster decision-making within a business. 

So how much do data engineers earn? It depends on a number of factors, but the average salary for big data engineers in the United States is $90,660 per annum, with a range of $62,676 - $140,373. Factors that affect the level of salary include job location, technical skills, on-the-job experience, and academic background. Salary and other facilities are largely dependent on your ability to deliver results, and level of experience. In the UK, an average salary of £33,971 per year can be expected, with a range of £17,265 - £60,621.

Job Description

Data engineers lead innovation through benchmarking, exploration, implementing big data technologies and making recommendations for platforms.  They are also engaged in developing and implementing of scripts for database monitoring, maintenance, performance tuning, etc. 

Typical Responsibilities:

  • Creating and maintaining data pipeline architecture
  • Assembling large, complex data sets that meet business requirements
  • Optimizing data delivery, automating manual processes and re-designing infrastructure for greater and faster scalability
  • Design, identification, and implementation of internal process improvements
  • Developing statistical learning models through research 
  • Keeping up-to-date with the latest trends and technology 
  • Collaborating with engineering departments and product management to devise solutions which meet business needs
  • Implementing new mathematical or other statistical methodologies 
  • Conducting analyses of statistical data to develop strategies
  • Managing analytics databases and implementing processes that lead to improved data quality 
  • Identifying trends and data patterns 
  • Creating, maintaining, and managing analytical data
  • Analyzing collected data to develop predictive models
  • Performing analysis of graphical models

Key Skills & Qualifications      
This field is relatively new, so education and training institutions are updating and expanding their offerings and programs to support a career as a data scientist. A degree in computer sciences, mathematics, computer engineering or statistics is required, and a post-graduate degree can be beneficial.

Required job skills:

  • In-depth knowledge of various database solutions and SQL  
  • Strong understanding of ETL tools and Data warehousing 
  • Experience in Hadoop based Analytics (Mapreduce, Hive, Hbase, etc.) 
  • Solid knowledge of various Operating Systems (UNIX, Linux, Solaris, etc.)
  • Excellent understanding of machine learning tools and techniques (e.g. ensemble methods, random forests, k-nearest neighbors, etc.) 
  • Software engineering skills (e.g. data structures, algorithms and distributed computing) =
  • Experience in NoSQL technologies (e.g. MongoDB and Cassandra) 
  • Capability of handling Data modeling tools (e.g. Visio, Enterprise Architect and ERWin)
  • Excellent analytic skills and capability in working with unstructured data sets 
  • Knowledge of highly scalable data stores, stream processing, and message queuing 
  • Strong organizational and project management skills 
  • Excellent Civil Service competencies, like partnering and collaborating 
  • Experience in data mining, predictive modeling, and data analysis techniques
  • Hands-on experience and familiarity with statistics and SQL software packages (SAS, R, Python) 
  • Expertise in relational database concepts and design 
  • Experience in logistic and genetic algorithms and statistical methods, decision tree analysis, PCA, and linear regression 
  • Experience in one or more programming languages (Java, Python, C/C++, Perl)
  • Great interpersonal and communication skills

 Job Trends  
It is expected that the career opportunities for data scientist will continue to increase in the coming years. Organizations are becoming more and more aware of the value of using big data to make informed, strategic business decisions and to see the big picture.