Lead the data engineering team in the design, development, and maintenance of our data warehouse, data lake, and associated data pipelines.
Champion the adoption of open-source data tools.
Make crucial decisions about data architecture and the selection of data processing technologies, driving the continual enhancement of our data engineering systems.
Foster a culture of collaboration, innovation, and continuous learning within the data engineering team, promoting best practices in data engineering.
Requirements
In-depth understanding of Data Language (T-SQL, PL/SQL, KQL).
Experience with open-source data processing tools such as MinIO, Hadoop, Apache Airflow, Apache Spark, and Apache Nifi is highly desirable.
Comprehensive knowledge of ETL/ELT processes and technologies.
Proven ability to make informed decisions concerning data architecture and technology selection.
Demonstrated leadership experience in a data engineering team, with excellent team management skills.
Robust communication skills, capable of effectively liaising with diverse stakeholders across the organization.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Ability to support data transformation, data structures, metadata, dependency, and workload management.
Ability to write effective and scalable Python codes Produce clean, consistent, logical code based on designs; submit to GitLab repository Generating infrastructure that allows big data to be accessed and analyzed.
+4 years of experience in a data engineering role.