Big Data Engineer

Responsibilities:

• As an Engineer you will be responsible for developing, deploying, maintaining / operating, testing and evaluating big data solutions within the organization
• Collect, store, process, and analyze of huge sets of data
• Choose optimal solutions to use for above purposes, then maintaining, implementing, and monitoring them
• Integrate solutions with the architecture used across the company.

Experience required:

• Mid/senior level, at least 3 years in working with Cloudera data platform

Technical skills:

• Programming experience, ideally in Python, Spark, Kafka or Java, and a willingness to learn new programming languages to meet goals and objectives
• Knowledge of data cleaning, wrangling, visualization and reporting, with an understanding of the best, most efficient use of associated tools and applications to complete these tasks
• Experience processing large amounts of structured and unstructured data, including integrating data from multiple sources
• Knowledge in configuring & troubleshooting of all the components in the Hadoop ecosystem like Cloudera, Cloudera Manager, HDFS, Hive, Impala, Oozie, YARN, Sqoop, Zookeeper, Flume, Spark, Spark standalone, Kafka (incl. Kafka Connect), Apache Kudu, Cassandra, Hbase
• Develop and maintain documentation relating to Hadoop Administration tasks (upgrades, patching, service installation and maintenance)
• Understand Hadoop’s Security mechanisms and implement Hadoop Security (Apache Sentry, Kerberos, Active Directory, TLS/SSL)
• Work and continuously improve the DevOps pipeline and tooling to provide active management of the CI/CD processes
• Should have experience in scripting for automation requirement (. scripting via Shell, Python, Groovy etc.)
• Understanding of networking principles and ability to troubleshoot (DNS, TCP/IP, HTTP).

Nice to have / a plus:

• Knowledge of one or more of the following: ElasticSearch, Kibana, Grafana, git/scm, Atlassian Suite (Confluence, Jira, Bitbucket) Jenkins/TeamCity, Docker and Kubernetes is highly appreciated
• NoSQL databases, MongoDB
• Integration with RDBMS, lambda architectures – integration of Data Warehouses – Data Lakes – Data Hubs
• Cloud implementations of Big Data stacks
• Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O.

Benefits:

• Interesting salary conditions
• Undetermined period of contract
• Career plan (professional, academic and financial)
• Medical insurance
• Lunch tickets
• Professional and friendly working environment.