Senior Data Engineer

BirBank is seeking a highly motivated and experienced Senior Data Engineers to join Data Technology team within Data Management Office. As Senior Data Engineer you will lead and oversee the data engineering team to design, build, and maintain scalable data infrastructure. You will be responsible for ensuring the smooth ingestion, processing, and storage of large-scale data sets, facilitating robust data analysis, and supporting data-driven decision-making across the organization.

Degree in computer science, information science, engineering, mathematics, or related technical discipline

5+ years experience with SQL and NoSQL technologies (Preferably Postgres and Oracle)

Hands-on experience with Apache Nifi ETL process design, implementation, and use of ETL tools

Hands-on experience with Airflow or similar Hands-on experience with Apache Spark

Hands-on experience with Greenplum administration

Experience in programming in Python, SQL, PySpark

Experience with data integration (ETL/ELT) concepts

Deep understanding of MPP architecture concepts

Experience with dbt modelling and SQL optimisation

Familiarity with lakehouse concepts and with version control tools

The following experience will be considered as an advantage:

Experience with AWS and/or GCP cloud services

Experience with data visualization tools (e.g. Tableau, PowerBI, etc.)

Understanding of DataOps and DevOps principles

Ability to create and maintain data pipelines

Knowledge of data modeling and database design

Experience with data engineering best practices, such as data security, data access control and data governance

Opportunities for professional growth and development

Competitive salary and bonuses

Comprehensive insurance coverage

Supportive work environment

Visa Premium salary card

Corporate discounts and events

Additional vacation days

Discounted education and employee loans

New cozy studio office in Port Baku Tower 2

Strong teamwork with Agile principles, regular team buildings and themed events

Multicultural environment with foreign colleagues sharing their best experiences

Designing a data lake to process and store an array of (un)structured data loaded from raw sources. Development of the data model - properly store the data and access it as needed for business purposes.

Development of the integration process - development of integration with various systems so that they can have a single view of key indicators when making decisions

Data preparation and ETL - development of a pipeline for extracting, transforming and loading data Developing and monitoring data pipelines to ensure data quality and integrity.

Automation and optimization of the data transformation process.

Working closely with other teams in the organization to ensure data is available and accessible for analytics and decision-making

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