-Designing and developing high-level technical architectures for both streaming and batch processing systems to ensure scalability and efficiency.
-Creating reusable components, frameworks, and libraries at scale to empower analytics data products and accelerate development.
-Conducting proof-of-concepts (POCs) on emerging technologies and architectural patterns to stay ahead of industry trends.
-Collaborating with business and technology stakeholders to design and implement product features that align with strategic goals.
-Proactively identifying and resolving data management issues to enhance data quality and reliability.
-Cleaning, preparing, and optimizing large-scale data for seamless ingestion and consumption across platforms.
-Leading the implementation of new data management projects and restructuring existing data architectures for improved performance.
-Developing complex automated workflows and routines using advanced workflow scheduling tools.
-Establishing continuous integration, test-driven development, and production deployment frameworks to streamline delivery.
-Conducting collaborative reviews of designs, code, test plans, and dataset implementations to uphold data engineering best practices.
-Analyzing and profiling data to inform the design of scalable, high-performance solutions.
-Troubleshooting complex data issues through root cause analysis to resolve product and operational challenges preemptively.
-Partnering closely with product management to translate business requirements into actionable epics and deliverables.

-Familiarity with Snowflake for cloud data warehousing.
-Knowledge of Kafka for real-time data streaming.
-Experience with AWS Glue for ETL processes.
-Proficiency in Oracle or SQL Server databases.
-Background in API integration for seamless data connectivity.
-Hands-on experience with CI/CD automation tools like Jenkins.