Job – Cyclad

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Data Science

Senior Data Engineer

Published on: 1734652800

Project information:

Responsibilities:

Designing new solutions and coming up with initiatives for improvements to existing solutions within data platforms - both as part of orders coming from the business (functional changes) and from technology (architectural changes)
Development of data platforms and ETL/ELT processes: technical support and active participation in the development of data platforms.
Work on building and optimizing ETL/ELT processes that are responsible for processing large data sets.
Implement processes to ensure optimal data processing
Standardize and streamline technical processes: implementing and optimizing code, test and documentation management standards
Selecting and configuring tools and development environments that support data engineering processes to maintain code quality and facilitate code scaling
Ensure standards compliance and code review: responsible for applying existing platform development standards and monitoring the quality of delivered solutions
Work directly with technology as a Data Engineer and Data Analyst to maintain a high level of technology sophistication, understand current challenges, and drive improvements based on actual technical need
Act as a mentor to the team, providing subject matter support in the areas of solution design, code standardization, process optimization and best practice implementation

Closes in 74 days!

Location:

Salary:

up to 180 PLN NET/H

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Requirements:

Minimum 5 years of experience in designing and building Business Intelligence, ETL/ELT, Data Warehouse, Data Lake, Data Lakehouse, Big Data, OLAP class solutions
Practical knowledge of various relational (e.g., SQL Server, Oracle, Redshift, PostgreSQL, Teradata) and non-relational database engines (e.g., MongoDB, Cosmos DB, DynamoDB, Neo4j, HBase, Redis, InfluxDB)
Strong proficiency in SQL and Python (minimum 5 years of experience)
Familiarity with data engineering and orchestration tools, particularly Spark/Databricks (including structured streaming mechanisms, DLT, etc.), Hadoop/CDP, Azure/Fabric Data Factory, Apache Flink, Apache Kafka, Apache Airflow, dbt, Debezium, and more
Understanding of data governance, data quality, and batch/streaming data processing challenges
Knowledge of architectural patterns in data, including Data Mesh, Data Vault, Dimensional Modeling, Medallion Architecture, and Lambda/Kappa Architectures
Proficiency in using git repositories (Bitbucket, GitHub, GitLab)
Experience with data services on the Azure and/or AWS platforms
Flexibility, self-reliance, and efficiency, with a strong sense of responsibility for assigned tasks
Practical knowledge of English at a minimum B2 level (C1+ preferred)