Cient is developing a system of record for the diamond supply chain. A critical part of this is the diamond matching project.
We are seeking a Data Engineer to own and architect the end-to-end reporting lifecycle, that’s still in an early MVP stage. You will inherit a replicated production environment and be responsible for transforming raw Python application data into a high-performance analytics layer. You will bridge the gap between backend data structures and business-ready visualizations.

• Advanced SQL knowledge (window functions, CTEs, optimization queries)

• Advanced knowledge of Data Build Tool (dbt) (or similar)

• Working knowledge of code versioning and peer code reviewing process.

• Working knowledge of deduplication and normalization strategies

• Working knowledge of Cloud infrastructure

• Working knowledge of Python coding principles and data libraries

• Knowledge of ORMs such as SQLAlchemy

Extra points for

• Knowledge of ML tooling, such as MLFlow and Sagemaker.

• Experience with AWS.

What you'll be doing:

• Building and maintaining a robust, end-to-end data and analytics platform.

• Developing and optimizing data pipelines to move data from online environments to the data warehouse and reporting layers.

• Writing high-quality, production-ready code in SQL and Python, utilizing libraries such as pandas and SQLAlchemy.

• Troubleshooting and resolving issues related to cloud data configuration, synchronization, and data latency.

• Managing and processing diverse data types, including both structured and unstructured data, such as JSONB.

• Designing, deploying, and maintaining automated business intelligence dashboards and internal monitoring tools.