Data Engineer

🚀 We are looking for a Middle+/Senior Data Engineer to join a long-term data platform project.

 

The role is focused on designing, building, and maintaining reliable data pipelines and cloud-based data platforms for high-load business environments. The ideal candidate has strong hands-on experience with Python, SQL, ETL/ELT processes, and AWS data services.

🎯 Responsibilities

 

- Design, build, and maintain scalable batch and near-real-time data pipelines.

- Develop ETL/ELT workflows using Python, SQL, and modern data engineering tools.

- Integrate data from APIs, databases, files, SaaS platforms, and event-based sources.

- Build and support data lakes, data warehouses, and analytics-ready datasets.

- Improve pipeline performance, reliability, scalability, and cost efficiency.

- Implement data quality checks, monitoring, logging, validation, and alerting.

- Troubleshoot production data issues and identify root causes.

- Collaborate with data analysts, BI engineers, data scientists, software engineers, and business stakeholders.

- Maintain technical documentation, data models, and pipeline specifications.

- Contribute to CI/CD, infrastructure automation, and cloud platform improvements.

 

🧩 Requirements

 

- 3+ years of commercial experience in Data Engineering or a closely related role.

- Strong hands-on experience with Python.

- Strong SQL skills, including complex transformations and query optimisation.

- Practical experience building and maintaining production-grade ETL/ELT pipelines.- Experience working with AWS data services, particularly S3 and at least one of the following:

  - AWS Glue;

  - Athena;

  - EMR;

  - Redshift;

  - Lambda.

- Experience with at least one orchestration or transformation tool such as Airflow, dbt, Prefect, Dagster, or similar.

- Experience working with at least one cloud data warehouse or data platform such as Snowflake, Databricks, BigQuery, or Redshift.

- Strong understanding of data warehousing, data lakes, data modelling, partitioning, and file formats.

- Experience implementing data quality checks, monitoring, and error handling.

- Experience with Git and CI/CD workflows.

- Ability to independently investigate issues, make technical decisions, and take ownership of delivery.

- English level: Upper-Intermediate or higher.

 

🧩 Nice to Have

 

- Experience with Spark or PySpark.

- Experience with Kafka, Kinesis, Pub/Sub, or other streaming technologies.

- Experience with Delta Lake, Apache Iceberg, or Apache Hudi.

- Experience with Terraform, AWS CDK, or another Infrastructure as Code tool.

- Experience with Docker or Kubernetes.

- Experience with high-load or analytics-heavy products.

- Experience with GCP or Azure data services.

- Experience supporting AI/ML or LLM-related data pipelines.

🧩You'll have an opportunity to:

Build scalable data platforms using modern cloud technologies.

Work with large datasets and production-grade data pipelines.

Collaborate with experienced international engineering teams.Solve complex data engineering challenges across different industries.

Continuously develop your technical expertise with modern data tools and cloud services.

Take ownership of features and contribute to high-quality engineering practices.