Data Engineer

Reposted 4 Days Ago
Be an Early Applicant
3 Locations
Remote
Mid level
Fintech • Payments
The Role
Design, build, and maintain AWS-based lakehouse solutions and medallion architecture using Iceberg and Glue. Implement CDC and streaming ingestion with Debezium and Kafka. Develop PySpark batch/distributed jobs on EMR/Glue, orchestrate workflows with Airflow, ensure data quality/governance, and collaborate on infrastructure and IaC practices to deliver reliable business-ready datasets.
Summary Generated by Built In

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 Way: Enjoy a SportsBenefits membership giving you access to a wide variety of gyms and sports facilities to support your active lifestyle.
  • Drive in Style:  After one year with us, you may be eligible for a company car—performance and availability permitting. 
  • Park with Ease: Complimentary parking space just steps from the office, so your commute is as smooth as your workday.
  • Max Out Your Downtime: 25 days of vacation + public holidays, plus an additional 10 sick days.
  • Shop & Save: Exclusive local discount card + tickets for exciting events like Beonix, basketball games, and more. 
  • Speak Like a Local: Join free Greek language classes, twice a week, open to all team members. 
  • Celebrate Together: We bring colleagues from all offices together for unforgettable company celebrations.
  • Global Collaboration & Events: Opportunities to participate in international company events and initiatives, connecting with colleagues from all regions and contributing to a truly global community

👉Please note that if you will be hired in Poland or Portugal, your assigned Talent Acquisition Partner will walk you through the specific working arrangements and any applicable conditions during the process.

🚀 Our Hiring Process:

  1. Step 1 – Thinking in Action (45 minutes): Your first conversation will be with our Talent Acquisition team. We'll explore your background, career journey, motivations, and overall fit for the role. As part of this discussion, you'll also complete a short technical screening that will be reviewed by our engineering team. This stage helps us understand both your experience and how you approach technical challenges.
  2. Step 2 – Build in Production (60–90 minutes): Meet with the Hiring manager and technical experts for a practical assessment. Depending on the role, this may involve a live coding exercise or a real-world scenario designed to evaluate your technical skills, problem-solving approach, and ability to work through challenges similar to those faced by our teams.
  3. Step 3 – Final Interview (45 minutes): The final stage is a group interview with senior members of our Technology squad, which may include the CTO and Head of Engineering. Together, we'll discuss team fit, collaboration style, expectations from both sides, and any remaining questions about the role, team, or technology domain. This is also an opportunity for you to learn more about our culture and ways of working.

Let's embark on a journey to redefine the landscape of payments together. We're not just offering a role; we're inviting you to be a part of something bigger. Join our team, and let's innovate, disrupt, and lead the future of payments. Together, we can make an impact that resonates. Welcome to the team! 

Please review our Privacy Policy to understand how we process your personal data during the recruitment process: https://payabl.com/privacy-policy

Skills Required

  • Minimum 3+ years of experience in data engineering or related roles
  • Strong experience with SQL and data modeling for analytics and reporting
  • Strong programming experience with Python, ideally including PySpark
  • Experience designing and maintaining ETL/ELT pipelines in production environments
  • Experience with real-time or near-real-time data ingestion
  • Experience with Kafka or similar streaming technologies
  • Experience with CDC concepts and tools such as Debezium
  • Experience with data lake or lakehouse architectures on cloud platforms
  • Hands-on experience with AWS data services (S3, Glue Catalog, Glue Jobs, EMR, IAM)
  • Experience with Apache Iceberg, Delta Lake, or similar open table formats
  • Experience designing curated analytics layers (silver/gold) in a medallion architecture
  • Experience with orchestration tools such as Apache Airflow or Dagster
  • Experience working with relational databases such as MySQL, MariaDB, or PostgreSQL
  • Working knowledge of Unix/Linux environments and shell scripting
  • Understanding of data quality, governance, lineage, and production monitoring concepts
  • Experience with Apache Druid, ClickHouse, Snowflake, or Databricks
  • Experience with Airbyte or similar data integration tools
  • Experience with dbt or collaboration with analytics engineering teams
  • Experience with Terraform and Terragrunt
  • Experience with Docker and Kubernetes
  • Experience optimizing Spark jobs on EMR or AWS Glue
  • Experience with data visualization tools such as Tableau, Power BI, Superset, AWS QuickSight
  • Experience with data observability, alerting, and monitoring tools
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The Company
HQ: London
151 Employees
Year Founded: 2011

What We Do

We are payabl., a paytech expert empowering merchants to take, make and manage payments globally. Our full solution stack includes card acquiring, alternative payment methods, payment accounts and prepaid cards. Welcome to payabl., where we take care of the payments, so you can take care of business. #payments #paytech #fintech

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