Chief Data Asset Developer

As a Data Engineer, you will be responsible for designing, developing and maintaining data assets and related products.

• Work with stakeholders to understand data requirements to design, develop and maintain complex ETL processes.
• Create data integration and diagram documentation.
• Lead validation, UAT and regression testing for new data asset creation.
• Create and maintain data models, including schema design and optimization.
• Develop pipelines that automate data flow, ensuring quality and consistency.

Strong knowledge of Python and Pyspark is required. You should also have skills in SQL, Hadoop, Hive, Azure, Databricks and Greenplum.

Familiarity with big data technologies like Hadoop, Spark and distributed computing frameworks is essential. Use Hue to run Hive SQL queries and schedule Apache Oozie jobs to automate data workflows.

Strong problem-solving and troubleshooting skills are expected. Establish comprehensive data quality test cases and implement automated validation processes.

A degree in Data Science, Statistics, Computer Science or related fields is required. 4-7 years of experience as a Data Engineer is necessary.