Interact with senior stakeholders on regular basis, to drive their business towards impactful change.
Become the go-to person for end-to-end data handling, management and analytics processes.
Work with Data Scientists to take data throughout its lifecycle - acquisition, exploration, data cleaning, integration, analysis, interpretation and visualization.
Become part of a fast-growing international and diverse team.
What you will do
Collaborate and work closely with teams to better understand the end-user requirements.
Design, develop, and maintain data pipelines using Azure Data Factory and other technologies, ensuring efficient and cost-aware processes.
Monitor and troubleshoot data pipeline performance, identifying and resolving issues promptly.
Work with Azure Data Lake Storage and Snowflake through dbt to manage and store large datasets, ensuring data is easily accessible and well-organized.
Implement data quality and data governance best practices to ensure the accuracy, consistency, and security of data.
Work closely with data scientists to understand their data requirements and provide the necessary support for their analytics and machine learning tasks.
Stay updated with the latest trends and advancements in data engineering, cloud technologies, and big data tools.
Create and maintain documentation related to data pipelines, data storage, and data processing workflows.
What you’ll bring
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Minimum of 1-2 years of experience in a data engineering role.
Proficiency in SQL and Python.
Experience with Snowflake or other pay-as-you-go DWH technologies.
Familiarity with big data technologies and distributed processing tools.
Understanding of data integration and ELT processes.
Good problem-solving skills and the ability to work collaboratively in a team environment.
Good to have
Experience with Azure data tools, including Data Lake, Data Factory and Azure Functions.
Experience with GitHub Actions for CI/CD pipeline implementation.
Knowledge of data quality and data governance best practices.
Experience with real-time data processing and streaming analytics.
Understanding of the energy sector and related data challenges.