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Sigma Software is seeking a Middle Data Engineer to join a remote team building modern cloud-native data platforms. You will develop and optimize ETL/ELT pipelines, data models, and architectures using Databricks, Apache Spark, Snowflake, and AWS to enable analytics and BI.
Ideal candidates have 3+ years in data engineering or software engineering, strong Python and SQL skills, and hands-on experience with cloud data warehousing.
Python / strong
SQL / expert
Apache Spark / strong
Databricks / strong
Snowflake / good
Do you enjoy building scalable data solutions that enable analytics, reporting, and business intelligence? We are looking for a Middle Data Engineer to join a remote team working on modern cloud-native data platforms and distributed data processing systems.
In this role, you will contribute to the development and optimization of ETL/ELT pipelines, data models, and cloud-based data architectures using technologies such as Databricks, Apache Spark, Snowflake, and AWS. This opportunity is ideal for engineers who want to deepen their expertise in modern Data Engineering practices while working on impactful business solutions.
We at Sigma Software value collaboration, continuous learning, and technical excellence. Joining our team means working in a supportive engineering environment with opportunities for professional growth, knowledge sharing, and long-term career development.
Our customer operates within a modern data-driven environment focused on analytics, reporting, and operational decision-making. The platform ecosystem combines cloud-native technologies, distributed processing frameworks, and scalable infrastructure to support reliable and high-performance data solutions.
The project focuses on building and maintaining scalable cloud-based data platforms that support analytics and business intelligence initiatives. The team develops ETL/ELT pipelines, optimizes data transformations, and enhances modern data architectures using distributed data processing technologies and cloud infrastructure.
Key Technologies: Python, SQL, Apache Spark, Databricks, Snowflake, AWS, ETL/ELT, CI/CD
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