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.
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.
