This is a remote position. ​Job description: 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.

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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

Dagster).

• 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.