Key Responsibilities
· Lead, mentor, and grow a team of high-performing data engineers. You will be responsible for maintaining a high standard of engineering excellence.
· Act as the primary technical point of contact for external SI partners. You will oversee their deliverables, ensure they adhere to our architectural standards, and manage the transition of knowledge from consultants to the internal team.
· Design and oversee scalable data ecosystems on AWS or Azure, ensuring seamless integration between legacy systems and modern cloud warehouses.
· Collaborate with UI/UX and BI teams to design last-mile data delivery. You ensure that the underlying data structures are optimized for rapid, clear visual representation layers (Power BI, Tableau, etc.).
· Architect the flow between SAP Datasphere and cloud-native environments to provide a unified Single Source of Truth.
· Design and oversee the development of feature stores and automated data pipelines specifically tailored for Machine Learning workflows.
Required Qualifications
· 10+ years in Data Engineering, with 3+ years in a leadership role.
· 8+years of hands-on experience as a Data Scientist or ML Engineer. You must understand model lifecycles, cross-validation, and the nuances of training/test data splits.
· Expert-level proficiency in AWS (Glue, SageMaker, Redshift) or Azure (Data Factory, Azure ML, Synapse/Databricks).
· Proven ability to manage System Implementation (SI) partners, holding them accountable for high-quality architectural outcomes.
· Experience building data models optimized for BI tools;
· Mastery of Python (for both Spark and ML libraries like Scikit-Learn/TensorFlow) and expert SQL.
· Experience in Oil and Gas industry
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