Middle Data Engineer

Vertex Technologies

Your Responsibilities

• Design, build, and maintain robust ETL/ELT pipelines using tools such as Databricks, Apache Spark, dbt, and Snowflake.
• Ingest and process data from APIs, message queues, relational databases, and files into a cloud-based data platform.
• Schedule and orchestrate workflows using Apache Airflow or cloud-native alternatives.
• Enable querying and analytics on large-scale data using data warehouses and SQL engines (e.g., Snowflake, BigQuery, Redshift).
• Operate across major cloud platforms (AWS, GCP, Azure) and leverage their native data engineering services.

What we offer

• Long-term stability, competitive compensation, and a fast onboarding process.
• Conditions for steady career development.
• Development supported by dedicated mentors and a variety of programs focused on expertise and innovation.
• A well-equipped and cozy office supports comfort and productivity across all project stages.
• Welcoming atmosphere and a friendly corporate culture.

Your Skills

• 2+ years of experience in data engineering
• Proficient in Python; knowledge of Scala is a plus.
• Experience with Databricks, Snowflake, or other modern data platforms.
• Strong command of SQL and familiarity with relational databases (PostgreSQL, MySQL, SQL Server).
• Exposure to one or more cloud platforms, ideally with services such as:
• AWS: Glue, Athena, Lambda, DMS, ECS, EMR, Kinesis, S3, RDS
• GCP: Dataflow, BigQuery, Cloud Functions, Datastream, Pub/Sub, Dataproc, Dataprep
• Azure: Data Factory, Synapse Analytics, Azure Functions, Data Explorer, Event Hubs, Data Wrangler

Nice to Have

• Experience with Delta Lake, Apache Iceberg, or other lakehouse formats.
• Familiarity with NoSQL databases (e.g., MongoDB).
• Knowledge of CI/CD for data pipelines, version control, testing frameworks.
• Comfort working with containerized or serverless environments (e.g., ECS, Cloud Run, AKS, Lambda).
• Hands-on experience with dbt Cloud/Core and integration into data workflows.