Middle Data Engineer

We are looking for a Middle+/Senior Data Engineer to join a long-term data platform project. The role is focused on building, maintaining, and optimizing scalable data pipelines, data warehouses, and cloud-based data platforms for high-load business environments.

The ideal candidate has strong hands-on experience with Python, SQL, Spark/PySpark, cloud data services, and modern ETL/ELT pipelines. Experience with AWS is highly important, while Databricks, Snowflake, BigQuery, dbt, Airflow, Kafka/Kinesis, and Terraform are strong advantages.

Responsibilities:

• Design, build, and maintain scalable batch and near-real-time data pipelines.
• Develop and optimize ETL/ELT workflows using Python, SQL, Spark/PySpark, Airflow, dbt, or similar tools.
• Work with cloud-based data platforms and services, especially AWS.
• Build and support data lakes, lakehouse architectures, and data warehouses.
• Integrate data from APIs, databases, SaaS tools, files, and streaming/event-based sources.
• Optimize data processing performance, query execution, partitioning, and storage costs.
• Ensure data quality, reliability, monitoring, logging, and validation across pipelines.
• Collaborate with engineers, analysts, BI teams, data scientists, and business stakeholders.
• Support documentation, data modeling, and data dictionary creation where needed.
• Contribute to CI/CD, infrastructure automation, and cloud data platform improvements.

Requirements:

• 3-5 years of experience in Data Engineering or closely related roles.
• Strong hands-on experience with Python, SQL, and Spark/PySpark.
• Experience building and maintaining production-grade ETL/ELT pipelines.
• Strong understanding of data warehouses, data lakes, lakehouse architectures, and data modeling.
• Experience with AWS data services such as S3, Glue, Lambda, Athena, EMR, Redshift, Firehose, Kinesis, SQS, or EventBridge.
• Experience with orchestration and transformation tools such as Airflow, dbt, Prefect, Dagster, or similar.
• Experience with at least one modern data platform: Databricks, Snowflake, BigQuery, Redshift, or similar.
• Understanding of data quality, monitoring, observability, and performance optimization.
• Experience with Git, CI/CD, Docker, Terraform, AWS CDK, or other DevOps/IaC tools.
• Ability to work independently, communicate clearly, and take ownership of delivery.
• English level: Upper-Intermediate or higher.

Nice to Have:

• Experience with Kafka, Kinesis, Pub/Sub, or other streaming/event-driven technologies.
• Experience with Delta Lake, Iceberg, Hudi, or other lakehouse table formats.
• Experience with Kubernetes.
• Experience in high-load, fintech, healthcare, telecom, eCommerce, SaaS, or analytics-heavy products.
• Experience with BI/reporting tools such as Tableau, Looker, Metabase, Power BI, or similar.
• Exposure to AI/ML or LLM-related data workflows.
• Experience with GCP or Azure data services.

We Offer:

• Paid vacation and sick leave
• We provide the equipment you need to work comfortably (if required)
• We cover 50% of courses if you want to grow professionally
• Regular salary reviews based on your performance
• Competitive salary, depending on your experience
• Always on-time payments — no delays
• A normal, supportive team without unnecessary bureaucracy