- Data Architecture: Develop, construct, test, and maintain data architectures, including databases and large-scale processing systems.
- Data Quality: Recommend and implement strategies to enhance data reliability, efficiency, and quality.
- Data Unification: Enable the integration of disparate data sets using various languages and tools to prepare data for correlation by data scientists.
- Data Support: Provide effective data architectures that meet the needs of data scientists, stakeholders, and business environments.
- Integration: Facilitate integration capabilities for external tools to perform data ingestion, compilation, analytics, and visualization.
- Data Engineering Experience: 7 years of experience in Data Engineering or a related technical field.
- Expertise in SQL, Python and Informatica ETL development
- Data Modeling: Strong proficiency in data modeling techniques.
- Data Management: Ability to identify and implement the most suitable data management systems.
- Data Quality: Expertise in ensuring data quality and cleanliness, even when working with disordered data sets.
- Technical Skills: Demonstrated proficiency in a wide range of technical tools and technologies, including Snowflake, Informatica, IICS, GitHub, Oracle, ETL development and Python.
- Education: Bachelor's degree in statistics, mathematics, computer science, or engineering.
- Scripting: Proficiency in scripting languages for managing data flows and pipelines.
- Data Validation: Expertise in data query and validation techniques.
- Strong analytical and problem-solving skills.
- Excellent communication and interpersonal skills.
- Ability to learn new technologies and tools quickly.
- Attention to detail and commitment to quality.