Senior Python Engineer (Data Focus).

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 engineer with strong Python skills and experience designing and building scalable, data-intensive systems. The role focuses on developing reliable data pipelines, working with large volumes of data, and solving complex data processing, scalability, and performance challenges.

About the Role:

We are looking for a Senior Python Backend Engineer with strong experience designing scalable, data-intensive systems and working with large volumes of data.

You will take ownership of designing and building scalable data pipelines, processing large datasets, and developing reliable data infrastructure. You will work with batch and streaming data processing, large databases, and data lake/lakehouse solutions, driving technical decisions and collaborating closely with cross-functional teams.

This role offers the opportunity to apply your software engineering experience to complex data challenges while shaping the architecture, scalability, and long-term reliability of modern data platforms.

Key Responsibilities:

• Design, build, and optimize scalable batch and streaming data pipelines for processing large volumes of data.
• Develop reliable, production-grade Python solutions for complex data processing and transformation.
• Take ownership of designing and improving scalable data infrastructure, including data lake and lakehouse solutions.
• Work with large datasets and databases, optimizing data storage, processing, and query performance.
• Ensure data quality, consistency, and reliability across data processing systems.
• Drive monitoring, troubleshooting, and performance optimization of data pipelines and infrastructure.
• Contribute to data security, governance, and retention practices.
• Lead technical decisions, evaluate architectural trade-offs, and contribute to data migration and platform development.
• Collaborate with Data Engineering, Backend, DevOps, Data Science, and other teams to deliver scalable and reliable data solutions.

Required Competence and Skills:

• 5+ years of hands-on experience in Python Backend Engineering, building scalable, data-intensive applications or systems.
• Strong experience designing, building, and optimizing data pipelines, including batch or streaming processing.
• Experience working with large volumes of data and solving challenges related to data processing, scalability, storage, and performance.
• Experience designing or working with data lakes, data warehouses, or lakehouse architectures.
• Experience designing, building, and optimizing batch and streaming data pipelines, ensuring efficient and reliable data ingestion and processing at scale.
• Experience with Big Data processing tools such as Apache Spark, Hadoop, or similar technologies.
• Production experience with cloud object storage (AWS S3 or equivalent) and at least one analytics platform such as Snowflake, Databricks, BigQuery, or a similar solution.
• Strong SQL skills and solid understanding of relational databases, data modeling, and query optimization.
• Good understanding of data processing, ETL/ELT concepts, data integration, and data quality in large-scale systems.
• Ability to independently drive technical decisions, contribute to system architecture, and clearly explain design choices and trade-offs.

Nice to Have:

• Experience with workflow orchestration tools such as Airflow or Dagster.
• Experience with Apache Iceberg, Delta Lake, Hudi, or similar lakehouse technologies.
• Experience with data governance practices, including metadata, lineage, PII protection, access controls, and retention.
• Experience working with financial, transactional, gaming, banking, or other regulated and data-intensive domains.

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.