Data Engineer

payabl. empowers businesses to grow through payments innovation and banking services. Our ambition is to expand our strong portfolio of global financial services we provide to businesses and make them all available in one place on our platform we call payabl.one. As a licensed financial company with principal membership with card schemes, we specialize in global payments and providing businesses with multi-currency accounts.

The role is about

Working as part of our Data Team to build and maintain reliable data pipelines and datasets that support analytics and decision-making across the organization. You will work with SQL, Python, cloud data platforms, batch and streaming pipelines, and modern data engineering technologies.

You will collaborate with engineers, analysts, and business teams to understand data requirements, improve data quality, and make data easier to consume. We are looking for someone with strong data engineering fundamentals who is curious, enjoys solving problems, and is interested in developing their skills across modern data platform technologies.

Location: Remote – Poland or Portugal | On-site – Cyprus

Reporting to: Head of Engineering

What you will do

Data Pipelines and Data Platform

• Build and maintain reliable ETL/ELT data pipelines using SQL and Python.

• Develop and maintain datasets used for analytics, reporting, and other business use cases.

• Work with batch and streaming data pipelines running on AWS.

• Contribute to the continuous improvement of our data platform, architecture, and engineering practices.

Data Modelling and Business-Ready Data

• Work with analysts, engineers, and business teams to understand data requirements and translate them into technical solutions.

• Develop well-structured and reusable datasets that make data easier to consume across the organization.

• Support data transformations and data modelling for analytics and reporting use cases.

• Contribute to improving the consistency, usability, and reliability of business data.

Data Quality and Production Reliability

• Support data quality checks and validation processes to ensure reliable and consistent datasets.

• Monitor data pipelines and help identify and troubleshoot data or pipeline issues.

• Support production reliability and investigate issues when pipelines or datasets do not behave as expected.

• Contribute to improvements in monitoring, observability, documentation, and data reliability practices.

Batch and Streaming Processing

• Work with batch and streaming data pipelines across the data platform.

• Support data processing and transformation workflows running on cloud-based infrastructure.

• Contribute to the development and maintenance of scalable and reliable data processing solutions.

Data Integration and Platform Development

• Work with data from relational and non-relational databases and other internal or external data sources.

• Support integrations and data ingestion workflows across different systems.

• Contribute to the evolution of the data platform as new requirements and technologies are introduced.

What we need

• 3+ years of experience in data engineering, software engineering, analytics engineering, or a related role.

• Good programming skills in Python and SQL.

• Experience building or maintaining ETL/ELT pipelines.

• Experience working with relational and non-relational databases such as MySQL, MariaDB, PostgreSQL, MongoDB or similar.

• Familiarity with cloud-based data platforms, preferably AWS.

• Understanding of basic data engineering concepts such as incremental processing, data quality, schema changes, and pipeline reliability.

• Comfortable working with Git and Unix/Linux environments.

• Good problem-solving and debugging skills.

• Willingness to learn new technologies and work across different parts of the data platform.

Good to Have

You do not need experience with all of the technologies below. Experience with one or more would be beneficial:

Data Processing and Cloud

• You do not need experience with all of the technologies below. Experience with one or more would be beneficial:

• Data Processing and Cloud

• Apache Spark or PySpark.

• AWS services such as S3, Glue, EMR, IAM, or Athena.

• Data lake or lakehouse architectures.

• Apache Iceberg, Delta Lake, Hudi, or another open table format.

Streaming and Data Integration

• Apache Kafka or another streaming platform.

• Change Data Capture concepts or tools such as Debezium.

• Airbyte or other data integration platforms.

Orchestration and Data Architecture

• Apache Airflow, Dagster, or another workflow orchestration tool.

• Medallion architecture concepts such as bronze, silver, and gold data layers.

• DBT or experience working with analytics engineering teams.

Infrastructure and Engineering

• Terraform, Terragrunt, or other infrastructure-as-code tooling.

• Docker or Kubernetes.

• Data quality, observability, monitoring, lineage, or governance tooling.

Analytics and Data Platforms

• Analytical databases or platforms such as Apache Druid, ClickHouse, Snowflake, or Databricks.

• BI or visualization tools such as Tableau, Power BI, Superset, or QuickSight.

What you can expect to work with

Our data platform includes technologies such as AWS, S3, Apache Iceberg, AWS Glue, EMR, Apache Kafka, Debezium, Kafka Connect, Apache Airflow, Airbyte, PySpark, Terraform, and Kubernetes.

You are not expected to know all of these technologies before joining . We value strong data engineering fundamentals, problem-solving skills, and the ability to learn and adapt.

The perks of being a payabl.er in Cyprus Office

• Future-Proof Your Finances: Once you’ve passed probation, we’ll kickstart your Provident Fund to secure your future.

• Grow with Us: Annual Learning Budget for professional development (eligible after probation)—because your growth is our growth.

• Wolt Your Way Through Lunch: €150 monthly Wolt allowance to keep you fueled and happy.

• Stay Active Your