Position: Strong Middle/Senior Data Engineer
Company: Intellias
Experience required: 5y
English level: upper

The company is supported by a robust ecosystem of technology partners, proven methodologies, and well-documented best practices. Thereby, elevating customers by achieving operational excellence on the cloud, within a secure environment, at every milestone of the journey to becoming cloud-first.
With over 12 years of experience and a portfolio with thousands of successful cloud deployments, the company serves clients across the globe. The company has offices in Israel, Europe, and North America.


Requirements:
• 5+ years of experience in a Data Engineer role in a cloud-native ecosystem.
• Bachelor (Graduate preferred) degree in Computer Science, Mathematics, Informatics, Information Systems or another quantitative field.
• Working experience with the following technologies/tools: big data tools: Spark, ElasticSearch, Hadoop, Kafka, Kinesis, etc.
• Relational SQL and NoSQL databases, such as MySQL or Postgres and DynamoDB or Cassandra.
• Cloud data services (AWS most wanted as kinesis, EMR, Redshift, etc.)
• Functional and scripting languages: Python, Java, Scala, etc. Advanced SQL.
• Experience building and optimizing ‘big data’ pipelines, architectures, and data sets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ stores.
• Experience supporting and working with external customers in a dynamic environment.
• Articulate with great communication and presentation skills (german language is a plus).
• Team player that can train as well as learn from others.
• Advantage: Experience with various ML models for classification, scoring, and more.
• Advantage: Experience with Deep Learning Neural Networks (Convolution, NLP etc.).
Upper-Intermediate + English level

Responsibilities:
• Keep our customers’ data separated and secure to meet compliance and regulations requirements.
• Design, Build and Operate the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, cloud migration tools, and ‘big data’ technologies.
• Optimize various RDBMS engines in the cloud and solve customers' security, performance, and operation problems.
• Design, Build and Operate large, complex data lakes that meet functional / non-functional business requirements.
• Optimize various data types ingestion, storage, processing, and retrieval from near real-time events, and IoT, to unstructured data as images, audio, video and documents, and in between.
• Work with customers and internal stakeholders including the Executive, Product, Data, Software Development, and Design teams to assist with data-related technical issues and support their data infrastructure and business needs.