Required experience: 3 to 5 years in data engineering, data warehousing, or related field
Role overview
Responsibilities
Data Pipeline Development: Design, implement, and maintain robust and scalable data pipelines to extract, transform, and load data from various sources into our data warehouse or data lake.
Data Modeling and Warehousing: Collaborate with data scientists and analysts to design and implement data models that optimize query performance and support complex analytical workloads.
Cloud Infrastructure: Leverage Google Cloud and other internal storage platforms to build and manage scalable and cost-effective data storage and processing solutions.
Data Quality Assurance: Implement data quality checks and monitoring processes to ensure the accuracy, completeness, and consistency of data.
Requirements
Experience level of 3 to 5 years in data engineering, data warehousing, or a related field.
Experience with building data pipelines, reports, best practices and frameworks.
Experience with design and development of scalable and actionable solutions (dashboards, automated collateral, web applications).
Experience with code refactoring for optimal performance.
Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources.
Familiarity with non-relational data storage systems (NoSQL and distributed database management systems).
Strong proficiency in SQL, NoSQL, ETL tools, BigQuery and at least one programming language (e.g., Python, Java).
Proficiency in Big Query, Data Flow, Data Proc, Cloud Sql, Terraform etc.
Strong understanding of data structures, algorithms, and software design principles.
Experience with data modeling techniques and methodologies.
Proficiency in troubleshooting and debugging complex data-related issues.
Ability to work independently and as part of a team.
Nice to have
Experience with dashboarding tools like plx dashboard and looker studio
Zobhira
