Rivka Development
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About the Role
We are seeking a skilled Data Engineer to join our team and help design, build, and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate has strong experience working with Python, SQL, cloud-based data platforms, and modern data engineering practices.
This role requires a proactive professional who enjoys solving complex data challenges and collaborating across teams to deliver reliable and scalable data solutions.
Requirements
5+ years of professional experience in Data Engineering or related roles.
Strong Python programming skills, including experience with Pandas and NumPy.
Advanced SQL skills and experience working with relational databases.
Experience designing, building, and maintaining ETL/ELT pipelines.
Hands-on experience with AWS data platforms, including Amazon S3 and Data Lake architectures.
Familiarity with AWS services such as Glue, Athena, Lambda, Step Functions, and/or Redshift.
Experience integrating and consuming REST APIs.
Experience working with time-series datasets.
Knowledge of analytical data formats including Parquet, CSV, and JSON.
Experience using Docker-based development environments.
Proficiency with Git and collaborative software development practices.
Understanding of data quality, validation, monitoring, and observability concepts.
Strong problem-solving, attention to detail and analytical skills
Ability to work independently in a remote environment.
Effective collaboration skills.
Professional English communication skills.
Nice to Have
Experience in energy, power, electricity, or trading markets.
Experience supporting machine learning workflows and data science teams.
Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines.
Build and optimize data ingestion processes from multiple sources, including REST APIs, databases, and external systems.
Design, build, and optimize data ingestion and processing workflows using Python and SQL.
Develop and maintain data solutions leveraging AWS services and Data Lake architectures.
Work with structured and semi-structured data formats, including Parquet, CSV, and JSON.
Implement data validation, monitoring, and quality controls.
Optimize data models, queries, and storage solutions for performance and scalability.
Collaborate with cross-functional teams to deliver reliable and scalable data solutions.
Support analytics, reporting, and machine learning use cases.
Fully Remote Opportunity
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