Position: Data Engineer
Company: Hedgehog
Category: Sysadmin
Experience required: 3y
English level: upper
Published: 2021-02-01T00:00:00+02:00

Required skills

The ideal candidate has:
• 3+ years of experience working on solutions that collect, process, store, and analyze the huge volume of data, fast-moving data, or data that has significant schema variability
• Proficient experience in distributed computing principles and familiar with key architectures including Lambda and Kappa architectures, and has a broad experience across a set of data stores (e.g., HDFS, Azure Data Lake Store, Azure Blob Storage, Azure SQL Data Warehouse), messaging systems (e.g.,Apache Kafka, Azure Event Hubs, Azure IoT Hub) and data processing engines (e.g., Apache Hadoop, Apache Spark, Azure Data Lake Analytics, Azure HDInsight)
• Experience in SQL migration on-premises to cloud, data modernization and migration, advanced analytics projects
Non-technical skills:
• Technical recommendations, problem-solving, risk management
• Proof of concept design, technical demonstration
• Consultative requirements clarification and issue troubleshooting
• Good written and spoken English

As a plus

Relevant Certifications (one or more will be a PLUS):
MCSA Cloud Platform Solutions Associate, Microsoft Certified DP-200,201, IBM Certified Data Architect/Engineer, Oracle

We offer

Great compensation and individual bonus remuneration
• Opportunities for professional growth and international certification
• Technical and business trainings and the best bootcamps (available worldwide online and onsite and covered by the company)
• Individual development plan
• Team buildings and corporate activities
• Innovative data projects and practical experience with cutting-edge technologies for various customers worldwide
• Long-term employment
• Comfortable office, 6 min. to the nearest metro station ’Kontraktova Ploscha’

Responsibilities

The Data Engineer is responsible for helping to select, deploy and manage the systems and infrastructure required of a data processing pipeline in support of the customer requirements.
Primary responsibilities revolve around DevOps and include implementing ETL (extract, transform and load) pipelines, monitoring/maintaining data pipeline performance.