Senior Data Engineer @ Mindbox S.A.

We are looking for a Senior Data Engineer to join a long-term project for our client, a digital-first bank focused on building the next generation of global financial services.

As part of a fast-paced technology team, you will contribute to the development and support of modern digital solutions that power new products and enhance existing ones. This role plays a key part in delivering scalable, end-to-end data capabilities across global business lines and functions.

If you're passionate about data engineering, enjoy working with modern technologies, and want to help shape the future of digital banking, we’d love to hear from you.

• Excellent experience in the Data Engineering lifecycle, building data pipelines that cover all stages from generation, ingestion, transformation to serving
• Strong experience with the Hadoop ecosystem and on-premises distributions, especially Cloudera, including HDFS, HIVE, Spark, Databricks
• Extensive experience using Python, PySpark and the Python ecosystem with good exposure to Python libraries
• Experience developing in other languages such as Scala or Java
• Proven experience building robust production data pipelines using Airflow (preferred)
• Exposure to running and maintaining ML models and MLOps (preferred)
• Experience with data lake formation, data warehousing principles, data modeling, schema design, and working with semi-structured and structured data
• Good understanding of file formats such as Parquet, ORC, Avro and their advantages and disadvantages
• Strong experience in SQL and building data analytics solutions
• Experience with one or more cloud service providers : AWS, Azure, or GCP (GCP preferred)
• Experience migrating on-premises solutions to cloud ecosystems (preferred)
• Good understanding of differences and trade-offs between SQL and NoSQL, ETL and ELT
• Understanding of containerisation and DevOps practices within modern data engineering
• Proven experience using version control tools such as Git within the development lifecycle
• Proven experience building CI / CD pipelines using tools like Jenkins, CircleCI, or GitHub Actions
• Nice to have : experience developing near real-time event streaming pipelines using Kafka, Spark Streaming, Apache Flink, Apache Beam, Google PubSub, or Google Data Flow

We are looking for a Senior Data Engineer to join a long-term project for our client, a digital-first bank focused on building the next generation of global financial services.

As part of a fast-paced technology team, you will contribute to the development and support of modern digital solutions that power new products and enhance existing ones. This role plays a key part in delivering scalable, end-to-end data capabilities across global business lines and functions.

If you're passionate about data engineering, enjoy working with modern technologies, and want to help shape the future of digital banking, we’d love to hear from you.

Work on engaging projects within one of the largest banks, contributing to the transformation of the financial services industry, Develop new and enhance existing financial and data solutions as part of the PSM engineering team, Participate in both greenfield projects and established Tier 1 bank applications used by millions of users, Support digital and data transformation through a continuous delivery model, Automate and optimize data engineering processes, Develop robust and fault-tolerant data solutions for both cloud and on-premise deployments, Work across various data, cloud, and messaging technology stacks, Learn and work with specialized data and cloud technologies to broaden skillset] Requirements : Python, Hadoop, Data engineering, Data pipelines, Cloudera, HDFS, Hive, Spark, Databricks, Scala, Java, MLOps, Data analytics, Airflow, PySpark, SQL, Cloud, Data modeling, GCP, Kafka, ETL, Jenkins, ML, AWS, Azure, NoSQL, DevOps, Git, CD pipelines, CircleCI, GitHub Actions, Apache Flink, Apache Additionally : Sport subscription, Private healthcare, Small teams, International projects.