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Data Engineer

Source Technology

Posted on Aug 24, 2021 by Source Technology

Zürich, Switzerland
Immediate Start
Annual Salary

Job Description

We are looking for a Data Engineer/Architect who will work on collecting, storing, processing, and analysing huge sets of data. The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, deploying, and monitoring them. You will also be responsible for integrating them with the architecture.

Your responsibilities:

  • Selecting and integrating Big Data tools and frameworks required to provide requested capabilities.

  • Implementing ETL processes.

  • Monitoring performance and advising necessary infrastructure and architectural changes.

  • Defining data retention policies.


Who you are:

  • You like to solve data problems and further develop them into production grade systems.

  • You have a profound knowledge in the area of data processing and data infrastructure.

  • You are analytically smart. You are comfortable with data and can use it to make decisions.

  • You are business smart. You see direct line from technical expertise to produce excellence to business success and understand the value of all three.


  • At least 4 years of practical experience as software engineer in the area of big-data processing preferably with a strong AWS background.

  • Considerable experience with Big Data Machine Learning toolkits, such as AWS Elastic Map Reduce, Mahout, SparkML.

  • Experience with building stream-processing systems, using solutions such as Amazon Kinesis, Kafka Stream processing, Storm or Spark-Streaming.

  • Experience with NoSQL databases, such as DynamoDB, HBase, Cassandra.

  • Experience with AWS public cloud and container-based systems like Docker and Kubernetes.

  • Considerable programming experience in Python and Java.

  • Ability to speak and write English fluently.

Tools and Technologies:
You have experience with, respectively you are interested in learning and improving your skills on the following technologies and tools:

  • Data infrastructure technologies with focus on AWS based solutions (S3, DynamoDB, RedShift, Hadoop).

  • Machine Learning technologies and services with focus on AWS based solutions (SageMaker, Jupyter Notebook)

  • Analytics technologies and services with focus on AWS based solutions (Athena, DataPipeline, Elastic Map Reduce)

  • DynamoDB, PostgreSQL and PostGIS respectively GIS

  • Stream processing with Apache Kafka

  • Docker, Kubernetes. Unix Shell (Bash), Python, Java and Kotlin.

  • JIRA, Git, GitLab, Bitbucket, Confluence, Slack

Reference: 1297238774

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