Data Engineer at Pezesha

Job Overview:

• We are looking for a rockstar Data Engineer who will report to the Data Science Lead. The owner of this role will be responsible for expanding and optimizing Pezesha’s data and data pipeline architecture, as well as optimizing data flow, model deployments and data storage for cross functional teams. They will support developers, database architects and data scientists during the full data and modeling lifecycle and will ensure optimal delivery and implementation of data projects.

Main responsibilities:

• Building and maintaining early stage data warehouses, setting up pipelines and deploying models, whilst ensuring data is securely and readily available to internal and external stakeholders(e.g. using modern data warehousing and database architecture)
• Identify, design, and implement internal process improvements, namely, automating manual processes, optimising data delivery, re-designing infrastructure for greater scalability.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Google BigQuery and Fusion technologies.
• Work with data scientists to design, build and implement analytics tools, reporting dashboards and models.
• Work with data and technology and assist with data-related technical issues and support data infrastructure needs.
• Support the development and management of CI/CD/CT pipelines for machine learning and other model iterations.
• Work with Data Scientists to ensure best data practices are used in model deployment and data management.

Core requirements:

We are looking for a candidate with experience or a strong interest in developing the following:

• 2+ years of experience building and maintaining early stage data warehouses, setting up pipelines and modeling analytical data (e.g. using modern data warehousing and database architecture principles).
• Understanding of the ETL cycle.
• Proficient in data analytics (BI reports, data insights).
• Knowledge of the data modeling lifecycle and an appreciation of the importance of metadata.
• Proficient in scripting languages (e.g. Python) and data statements (SQL) is a must..
• Experience (or a strong interest in) collaborating with technology and data science teams to design and implement scalable infrastructures for different types of structured and unstructured data.
• Interest in being part of a high-growth startup or tech company.
• Clear communication (in English) and ability to work well with others in a distributed team.

Experience (or an interest in learning) with the following technologies is desirable:

• Flask, Pandas, Scikit-Learn
• SQL, Postgres
• Google Biq Query