Data Engineer (Mid)

Alterdata.io is a data services company seeking a Mid Data Engineer contractor. The role involves engineering projects related to migrating data platforms to the cloud, building modern data warehouses, and designing and optimizing ETL/ELT integration pipelines. The company collaborates closely with Tech Leaders and Data Analysts to create scalable, efficient, and stable data infrastructure based on platforms such as GCP, AWS, Azure, Snowflake, and dbt. The infrastructure supports BI systems and AI/ML solutions.

• Commercial experience as a Data Engineer.
• Very good knowledge of Python.
• Proficiency in SQL including query writing, optimization, and database work (e.g., PostgreSQL, BigQuery).
• Understanding of ETL/ELT process management and orchestration.
• Experience integrating data from multiple sources (streams, relational databases, files, APIs).
• Practical experience with cloud platforms such as Google Cloud Platform or Azure.
• Knowledge of Data Warehousing, Data Lakes, and Data Lakehouse concepts.
• Experience implementing serverless solutions using containerization technologies (e.g., Docker).
• Knowledge of version control systems like Git and experience with code management platforms (GitHub, GitLab, Bitbucket).
• Good work organization and effective communication skills.
• English proficiency minimum at C1 level.

Nice to have:

• Familiarity with CI/CD tools (e.g., Jenkins, GitHub Actions, GitLab CI).
• Experience with Infrastructure as Code tools such as Terraform.
• Knowledge of real-time data processing tools like Apache Kafka, Apache Spark, Google Dataflow.
• Experience with tools like DBT, Dataform.
• Knowledge of data integration, storage, processing, and search tools such as Spark, Snowpark, AWS Data Migration Services, Azure DataFactory, Google DataFlow.
• Experience with platforms BigQuery and Snowflake.
• Experience using AI tools for coding assistance (e.g., Cursor, Claude Code).

• Independently execute data engineering tasks using cloud platforms such as GCP, Azure, and Snowflake.
• Implement and develop scalable ETL/ELT processes using dedicated cloud services.
• Build and maintain data pipelines in cloud environments (e.g., BigQuery, Pub/Sub, Composer, Data Factory, Functions).
• Develop efficient code and automation scripts in Python and SQL.
• Develop and optimize integration mechanisms for data from diverse sources including APIs and databases.
• Collaborate closely with cloud architects, analysts, and other data engineers to ensure high quality and stability of solutions.
• Prepare and update technical documentation for delivered solutions.
• Coordinate own tasks continuously.