Data Engineer

Creditsafe Group; Dublin; Hybrid; EUR 85,000 - 120,000; Full time

Benefits offered by this job

Bonus Scheme

Cycle to work

Global company gatherings

E-learning and career progression

Job summary

Creditsafe Group is building a new data and AI platform with data quality, lineage and auditability as core goals. The team will use AWS services like S3, Iceberg, Aurora, DynamoDB, Lambda, Fargate, ECS, Airflow, Spark and will integrate with Snowflake and Databricks to serve customers with high-throughput data insights.

You will work on end-to-end data pipelines, design scalable architectures, and contribute to AI capabilities on top of the platform, using Python and Terraform for

Qualifications

• Proven experience building production data pipelines in Python.
• Hands-on with modern cloud data platforms (Snowflake/Databricks).
• Strong understanding of data engineering best practices.

Responsibilities

• Contribute to codebase and participate in peer reviews.
• Design and build metadata-driven, event-based data processing pipelines.
• Integrate AWS data lake with Snowflake and Databricks.
• Design, develop and deploy scalable, low-latency data systems.
• Scale data pipelines with both batch and streaming approaches.
• Leverage AI tools to enhance data capabilities.

Skills

Python

Data engineering

Distributed systems

Cloud computing

Big data

Tools

Snowflake

Databricks

Terraform

Airflow

S3

DynamoDB

Iceberg

Lambda

Kinesis

Job description

With the largest owned database supported by a partner network, Creditsafe provides data on 320 million companies in over 100 countries to support its customers in this regard. Creditsafe is scaling business and currently going through a significant growth stage. Being a data company, Creditsafe collects and processes large amounts of complex data, received from multiple channels with the only purpose of serving our clients with opportunities to gain actionable insights. Our holistic data aggregation helps our clients to fill the knowledge gaps, influence decision making, and find hidden patterns.

This opportunity is to join a team of highly technically skilled engineers who are designing Creditsafe’s new data and AI platform with data quality, data lineage, and auditability as the primary goals whilst maintaining high throughput and scalability. The data platform will be built using AWS infrastructure such as S3, Iceberg, Aurora, DynamoDB, Lambda, Fargate, ECS, Airflow, Spark. A key aspect of this role with be helping to implement the integration of the AWS data platform across Snowflake and Databricks to meet the data needs of our customers in their native data cloud platform. The platform is expected to manage over one hundred million objects with a high volume of daily updates handling addition, deletion, and correction of our data and indexes in an auditable manner. We will also be building AI capabilities on top of these platforms based on MCP and AI agentic workflows. Our data processing application is entirely based on Python and we use Terraform to build re-creatable infrastructure.

What you will be doing?

• You will actively contribute to the codebase and participate in peer reviews.
• Help to design and build metadata driven, event based distributed data processing platform using technologies such as Python, Spark, Airflow, Iceberg, DynamoDB, AWS Glue, S3.
• You will work on integrating our AWS data lake with other data platforms such as Snowflake and Databricks.
• As an experienced Engineer, you will play a critical role in the design, development, and deployment of our business-critical system.
• You will be building and scaling Creditsafe’s data pipelines combining batch and streaming approaches and targeting sub-100ms latency serving.
• Understanding domain data to make recommendations to improve the existing product.
• Building AI-based solutions leveraging approaches such as semantic search, MCP and agentic workflows.
• Employing various AI tools such as Perplexity, Cursor, CoPilot, etc to aid in all aspects of your work.

What are we looking for?

• Track record of successfully implementing and operating production data platforms using Python and AWS.
• Hands-on experience with modern cloud data platforms including Snowflake and/or Databricks.
• You understand and can implement data engineering best practices.
• You demonstrate the ability to write clean & efficient code and combine it with the cloud environment for best performance.
• Proven experience of development experience within a commercial environment creating production grade data pipelines in python.
• We appreciate someone that is looking to grow your skills through daily technical challenges and enjoy problem solving, whiteboarding in collaboration with team.
• You have excellent communication skills, and ability to explain your views clearly to the team and are open to understanding the views of others.
• You share your ideas collaboratively via wikis, discussions boards, etc and share any decisions made, for the benefit of others.
• Be able to take ownership of end-to-end deliverables from planning all the way to production.

Why Creditsafe?

• Career Progression: Clearly defined career progression path with opportunities to grow as a technical leader or move into adjacent roles.
• Learning & Development: Access to a plethora of learning resources and courses to perpetually enhance your skills, with weekly dedicated training and focus time.
• Work-Life Balance: Committed to promoting a balanced lifestyle with flexible working hours and hybrid work options.
• Innovation: Engage in exciting projects, harnessing the power of the latest technologies in cloud computing and data management.

Our Technology Stack: Python, Linux, Airflow, AWS DynamoDB, S3, Glue, Athena, Redshift, lambda, API Gateway, Terraform, CI/CD

• Bonus Scheme
• Cycle to work and Wellbeing Programme
• Global Company gatherings and events
• E-learning and excellent career progression opportunities
• Plus more that can be found on the benefits section on the Careers page, https://creditsafecareers.kinsta.cloud/gb/