Senior Data Engineer - SOL-1634
Summary
Build and maintain scalable data pipelines and the Elastic Hierarchy framework using Python, AWS, Snowflake, and DBT to support analytics and ML in a hybrid SaaS/on-premise environment.
We are seeking a Senior Data Engineer to design, build, and maintain scalable data systems that support analytics and machine learning initiatives. This role operates within a SaaS and on-premise hybrid deployment environment and plays a key role in structuring and optimizing data flow across the platform. A core focus will be extending and operating the company’s Elastic Hierarchy framework.
Schedule: Full-time
Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python.
- Process and integrate data from multiple formats and sources, including JSON, CSV, and XML.
- Build and manage data transformations and orchestration workflows using DBT and tools such as Airflow, Prefect, or Dagster.
- Enforce data governance, quality, and security standards across data systems.
- Extend, maintain, and optimize the Elastic Hierarchy data framework.
- Collaborate closely with analytics, machine learning, and product teams to deliver reliable, business-ready datasets.
- Support data operations in SaaS and on-premise hybrid environments.
Requirements
Skills:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
- Strong proficiency in Python development.
- Experience with the AWS data ecosystem, including services such as S3, Glue, Lambda, EMR, EC2, Redshift, and RDS.
- Hands-on experience with Snowflake, MongoDB, and PostgreSQL.
- Experience using DBT and at least one data orchestration tool (Airflow, Prefect, or
- Knowledge of data mapping, attribution, and reconciliation processes.
- Ability to work effectively in hybrid and on-premise deployment environments.
- Strong English communication skills, both written and verbal.