Key Skills: Python (Strong), Advanced SQL, Airflow/Spark/Kafka, Cloud (AWS/Azure/GCP), Modern DW (Snowflake/Databricks), Data Pipeline ETL/ELT.
Core Domains: Proven experience building data applications, data warehouses, semantic models, and data integration layers.
Programming & Workflows: Strong familiarity with Python (or SQL-based workflows) to review pipeline logic and engage in technical code reviews.
Data Fundamentals: Core ETL/ELT pipelines, data modelling, data quality, and governance.
Cloud & Databases: Hands-on familiarity with cloud data platforms (Azure, AWS, or GCP) along with relational and non-relational database systems.
Qualifications:
A Bachelor’s or Master’s degree in any discipline from a recognized institution is acceptable.
Job Description:
Team Leadership & Development: Mentor and manage a team of data engineers, driving technical excellence and accountability.
End-to-End Delivery: Lead the delivery of data engineering, analytics, and platform initiatives from design to production.
Architecture Oversight: Guide the implementation of scalable data integration layers, enterprise data warehouses, semantic models, and analytics applications.
Project & Scope Governance: Own project scope, timelines, budgets, risks, and dependencies; proactively mitigate execution risks.
Cross-Functional Collaboration: Partner with Data Scientists, Architects, Product Managers, and Business Analysts to translate business goals into technical deliverables.
Sprint & Status Execution: Drive sprint planning, status tracking, stakeholder communication, and senior leadership reporting.