This is a remote position.
Job description:We are seeking a Senior Data Engineer to design, build, and maintain scalable data systems thatsupport analytics and machine learning initiatives. This role operates within a SaaS andon-premise hybrid deployment environment and plays a key role in structuring and optimizingdata flow across the platform. A core focus will be extending and operating the company’s ElasticHierarchy 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.
