Senior Data Engineer @ ITDS

ITDS

Kraków, małopolskie
Stała
Pełny etat

3 dni temu

You're ideal for this role if you have:

Strong experience in PySpark, Scala, or similar data engineering languages
Hands-on experience building production data pipelines using Hadoop, Spark, and Hive
Knowledge of cloud platforms and migrating on-premise solutions to the cloud
Experience with scheduling tools such as Airflow and workflow orchestration
Strong SQL skills and experience with data modelling and warehousing principles
Familiarity with Unix/Linux platforms and big data distributed systems
Experience with version control tools such as Git and CI/CD pipelines (Jenkins, GitHub Actions)
Understanding of ETL/ELT frameworks and data formats (Parquet, ORC, Avro)
Proven ability to troubleshoot, debug, and optimize data processing workflows
Experience working in Agile environments and collaborating across global teams

It is a strong plus if you have:

Experience with near real-time event streaming tools (Kafka, Spark Streaming, Apache Flink)
Exposure to MLOps or running machine learning models in production
Knowledge of DevOps practices, containerization, and cloud design patterns
Experience developing in Java or other programming languages
Familiarity with Elasticsearch and ingestion pipelines

Join us, and engineer robust systems for millions of users!Kraków - based opportunity with hybrid work model (6 days/month in the office).As a Senior Data Engineer, you will be working for our client, a global digital-first bank focused on delivering innovative financial solutions at scale. You will join a dynamic engineering team responsible for building and enhancing data solutions that support critical business applications used by millions of customers. Your role will involve developing robust and fault-tolerant data pipelines, automating processes, and supporting cloud and on-premise deployments. You will collaborate with engineers, data analysts, and business stakeholders to ensure data solutions are efficient, scalable, and aligned with the bank’s digital and data transformation initiatives.,[Designing, developing, and maintaining end-to-end data pipelines across cloud and on-premise systems , Implementing robust ETL/ELT processes using PySpark, Hadoop, Hive, and Spark SQL , Collaborating with engineers and analysts to translate requirements into scalable data solutions , Automating workflows and optimizing data engineering processes for efficiency and reliability , Ensuring data quality, accuracy, and consistency across pipelines and applications , Migrating on-premise data solutions to cloud platforms such as GCP, AWS, or Azure , Participating in code reviews, promoting development standards, and sharing knowledge with peers , Supporting production environments, troubleshooting issues, and monitoring performance and scale , Contributing to system architecture, design discussions, and Agile development processes ] Requirements: Data pipelines, Cloud, ETL, PySpark, Hadoop, Hive, Spark SQL, Data engineering, Cloud platform, GCP, AWS, Azure, Scala, Spark, Airflow, SQL, Data modelling, Unix, Linux, Git, CI/CD Pipelines, GitHub Actions, Spark Streaming, Flink, MLOps, Machine learning, DevOps, Design Patterns, Java, Elasticsearch, Kafka Additionally: Sport subscription, Private healthcare.

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