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 discipline5+ 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 toolsHands-on experience with Airflow or similar Hands-on experience with Apache SparkHands-on experience with Greenplum administrationExperience in programming in Python, SQL, PySparkExperience with data integration (ETL/ELT) conceptsDeep understanding of MPP architecture conceptsExperience with dbt modelling and SQL optimisationFamiliarity with lakehouse concepts and with version control toolsThe following experience will be considered as an advantage:Experience with AWS and/or GCP cloud servicesExperience with data visualization tools (e.g. Tableau, PowerBI, etc.)Understanding of DataOps and DevOps principlesAbility to create and maintain data pipelinesKnowledge of data modeling and database designExperience with data engineering best practices, such as data security, data access control and data governance Opportunities for professional growth and developmentCompetitive salary and bonusesComprehensive insurance coverageSupportive work environmentVisa Premium salary cardCorporate discounts and eventsAdditional vacation daysDiscounted education and employee loansNew cozy studio office in Port Baku Tower 2Strong teamwork with Agile principles, regular team buildings and themed eventsMulticultural 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 decisionsData 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
