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.
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