Middle Data Engineer.

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

Our client is a major online gaming operator building a next-generation transactional platform for user account management. This is a greenfield project designed to operate in a highly regulated, high-volume environment and support millions of concurrent users. The platform will process financial transactions in real time and must ensure high availability, sub-second performance, data integrity, security, and full auditability. One of the key engineering challenges is maintaining reliability and performance during extreme traffic spikes and peak events. 

The team is looking for a hands-on Data Engineer to help build and maintain scalable and reliable data infrastructure, develop production-grade data pipelines, and work with large volumes of business and transactional data, with a strong focus on data quality, integrity and performance.

About the Role:

You will contribute to the design, implementation, and operation of the data lake and lakehouse architecture, working closely with senior engineers on key technical decisions. This includes building and maintaining reliable data pipelines, working with large-scale business and transactional data, and supporting how data is stored, partitioned, processed, and monitored. You will work closely with Data Engineering, DevOps, Data Science, and other stakeholders to ensure data is accurate, reliable, and available for different use cases. You will also contribute to the data migration, help monitor data quality and pipeline health, and support the performance and long-term maintainability of the data infrastructure.

Key Responsibilities:

• Build, maintain, and optimize end-to-end data pipelines for processing large volumes of data.
• Develop and support data lakehouse solutions using Databricks, Apache Iceberg, and modern data technologies.
• Work with Python and SQL to develop data processing workflows and improve data quality.
• Support batch and streaming data ingestion, ensuring accurate and reliable data processing.
• Develop and improve ETL/ELT processes to support business and analytics needs.
• Work with large datasets, optimizing data storage, transformation, and query performance.
• Monitor data pipelines, troubleshoot issues, and improve system performance and reliability.
• Participate in data modeling and data integration tasks to support new features and business requirements.
• Contribute to improving existing data engineering solutions and implementing new functionality.
• Collaborate with Data Engineering, DevOps, Data Science, and Analytics teams to deliver reliable data solutions.

Required Competence and Skills:

• 3+ years of hands-on experience in Data Engineering, working with large datasets and data pipelines.
• Strong hands-on experience with Python for data processing and transformation.
• Experience building, maintaining, and optimizing end-to-end data pipelines in Big Data environments.
• Experience with Apache Iceberg or similar data lakehouse technologies, with a good understanding of modern data lakehouse concepts.
• Strong SQL skills and good understanding of relational databases and data modeling.
• Understanding of ETL/ELT processes, data ingestion, and transformation.
• Good understanding of data quality, pipeline monitoring, and performance optimization.
• Ability to work independently, solve technical problems, and collaborate effectively with the team.
• Understanding of data processing requirements in business environments, preferably involving transactional or financial data.

Nice to Have:

• Hands-on experience with Databricks.
• Experience with AWS (S3) or other cloud platforms.
• Familiarity with Kafka, Debezium, or other streaming and CDC technologies.
• Experience with workflow orchestration tools such as Airflow or Dagster.
• Experience working with financial, transactional, gaming, or other data-intensive domains.
• Experience participating in large-scale data migration or building a new data platform.

Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.