Senior Data Engineer for IT solutions company

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Project description:

• The client is a global IT services and solutions provider.
• You will be a part of an experienced team working in Agile methodology.

Requirements

Must-haves for this position

If you’re experienced with DE open-source solutions:

• event-driven architectures & pub-sub systems like Kafka,
• data processing with Spark framework with batching and streaming concepts,
• orchestrations and scheduling tools (e.g. Airflow),
• noSQL databases engines (e.g. Cassandra, Neo4j, MongoDB, ELK),

If you’re experienced with commercial DE solutions:

• big data infrastructures (e.g. Cloudera, Confluent, Databricks),
• data warehouses (e.g. BigQuery, Redshift, Snowflake),
• ETL low-code/no-code tools (e.g. Matillion, Talend),
• advanced experience with SQL,

Also, we’d expect from you:

• at least 3 years' practical experience in Data Engineering,
• knowledge & experience in data processing solutions (e.g. data lakes, data lakehouses, DWHs)
• experience with at least one of the following cloud infrastructures (AWS, Azure, GCP) and IaaC experience (e.g. terraform, Cloud Formation),
• experience in creating data architectures (data lakes, lambda, kappa) with strong responsibility from scratch,
• experience in programming with: Python or Scala,
• experience working with structured and unstructured data (AVRO, Parquet, JSON),
• practical experience with CI/CD, code coverage, code testing methodologies, OPP, functional programming, design patterns in software development,
• knowledge of Scrum and Agile methodologies,
• willingness to help and mentor other developers,
• familiarity with containerization (Docker, Kubernetes).

Benefits

In return, we offer:

• work with an experienced team and continuous development of your hard and soft skills;
• dev-friendly processes such as Continuous Integration, Continuous Delivery, Code Review and bug bashes;
• long-term collaboration on challenging products (FinTech, B2B software, E-commerce and more).

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