Compensation: $35k – $48k • No equity
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