Job overview
the ideal candidate will have a strong background in data engineering, with experience in building and maintaining large-scale data pipelines. The role involves supporting technical solutions implemented in the data lake, collaborating with data analysts and architects to validate solutions, and troubleshooting complex data engineering challenges.
key responsibilities:
* support data lake implementations: collaborate with data analysts and architects to implement and maintain data lake solutions, ensuring seamless integration with existing systems.
* build data pipelines: design, develop, and enhance data pipelines for extraction, transformation, and load from multiple data sources, utilizing various programming languages and technologies.
* manage data models: develop and maintain dimensional and normalized data models to support business intelligence analytics needs, working closely with stakeholders to ensure accurate data representation.
* collaborate with data analysts and scientists: support data analysts and scientists in developing optimized data models, pipelines, and frameworks, driving innovation and improvement in data-driven decision-making.
* troubleshoot data pipeline issues: identify and resolve complex data pipeline issues, leveraging expertise in data engineering to minimize downtime and maximize system availability.
required skills and qualifications:
* strong background in data engineering: proven experience in designing, developing, and maintaining large-scale data pipelines, with a deep understanding of data engineering principles and practices.
* programming languages and technologies: proficiency in one or more programming languages (e.g., python, java, scala) and technologies (e.g., apache beam, apache spark, aws glue), with experience in integrating them into data pipelines.
* data modeling and architecture: ability to design and maintain dimensional and normalized data models, with experience in data warehousing and business intelligence.
* collaboration and communication: excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams, including data analysts, scientists, and stakeholders.
benefits:
this role offers a dynamic and challenging work environment, with opportunities for professional growth and development. The successful candidate will be part of a collaborative team, working on innovative projects that drive business value and improve customer experiences.