Senior Data Engineer

Our client is a growing technology company developing market intelligence and software solutions. They are looking for a Senior Data Engineer to join a small international team and take ownership of complex data engineering challenges involving large-scale data processing, standardization, matching, and data quality.

The role is highly hands-on and suits an engineer who is comfortable working independently, making technical decisions, and taking solutions from initial design through reliable production delivery.

• →

  Design, build, and maintain scalable production data pipelines.

• →

  Ingest, process, and transform large volumes of data from multiple sources.

• →

  Develop solutions for data standardization, normalization, matching, and validation.

• →

  Build data quality controls and monitoring to identify malformed, inconsistent, or incorrect data.

• →

  Design reliable approaches to data corrections, updates, reprocessing, and backfills.

• →

  Improve the architecture, scalability, reliability, and performance of the data platform.

• →

  Take end-to-end ownership of technical solutions and production quality.

• →

  Work closely with a small engineering team while independently driving your area of responsibility.

• →

  Use AI-assisted engineering tools and practices to improve development efficiency.

• 4+ years of hands-on Data Engineering experience with production data systems.

• Strong Python skills.

• Hands-on experience with PySpark / Apache Spark and distributed data processing.

• Strong experience building and maintaining ETL/ELT and data ingestion pipelines.

• Experience working with large, complex datasets and multiple data sources.

• Strong SQL and data modeling skills.

• Experience with modern data platforms, data lakes, lakehouse, or similar architectures.

• Strong understanding of data quality, validation, monitoring, and data reliability.

• Ability to independently design solutions, troubleshoot production problems, and take ownership of delivery.

• Fluent English.

• Delta Lake experience.

• MongoDB experience.

• Databricks experience.

• Experience with data matching, reconciliation, deduplication, or complex standardization problems.

• Experience in a startup, scale-up, small product company, or lean engineering team.

• Docker, Linux, CI/CD, or related DevOps experience.

• Experience mentoring or technically supporting other engineers while remaining hands-on.

• Active use of AI coding tools or agent-based development practices.