About the role
TL;DR
Design, build, and optimize scalable data pipelines and enable AI use cases.
- •Join Odaseva's R&D team as a Data Engineer to shape the future of their data platform.
- •You will design, build, and optimize scalable data pipelines and contribute to their first AI use cases.
- •Key Responsibilities Design, build, and maintain ingestion/processing pipelines at scale using Python/SQL and Spark; operate within a lakehouse stack (Apache Iceberg or Delta Lake).
- •Implement and optimize workflows on Databricks and/or Snowflake.
- •Improve performance, reliability, and cost on AWS with strong observability and IaC practices.
- •Enable secure, efficient data access for customers via connectors, APIs, and lakehouse sharing patterns.
- •Prepare data for initial AI/ML use cases (feature pipelines, data quality, lineage).
- •Requirements 7–12 years in data engineering or backend data platforms.
- •Strong Python and SQL; experience with Spark and modern ELT/Orchestration (e.g., dbt, Airflow).
- •Hands-on with Databricks and/or Snowflake in production.
- •Experience on AWS (S3, Glue/Athena, Redshift, Lambda) and lakehouse formats (Iceberg or Delta Lake).
- •Proven experience with data modeling and cost management principles.
Required skills
PythonSQLSparkDatabricksSnowflakeAWSdbtAirflow
Nice-to-have skills
Azure
Benefits & perks
Remote work
Tech stack
PythonSQLSparkDatabricksSnowflakeAWSAzureS3RedshiftAthenadbtAirflowGit