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Tier-1 employer with senior, specialized DWH skills reduces but still attracts moderate applicant competition.
Specialized DWH and cloud platform skills are transferable across industries but remain domain-specific.
Explicit 8-10 years, mandatory DWH/cloud and specific tech stack enforce high filter.
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Design, develop, and maintain scalable, efficient data pipelines and processing platforms supporting Corporate Functional Data IT.
Lead technical proof-of-concepts and integrate AI/ML use cases (e.g., NLP to SQL conversational agents) to accelerate analytics and business insights.
Ensure data quality, governance, and collaboration across cross-functional teams to support data-driven decision-making and multiple corporate portals.
8-10 years of experience in Data Warehousing (DWH) with strong understanding of ETL processes and tools.
Bachelor’s degree in engineering, technology, or related field.
Expertise in cloud data platforms specifically Snowflake, ETL tools including Informatica and DBT, and data streaming technology Kafka.
Hands-on scripting/programming with Unix Shell Script, Python, SQL; experience with data quality tools like Snowflake DMF; familiarity with Git, CI/CD, Agile, Docker, Kubernetes, and DevOps.
Experienced technical leader capable of owning end-to-end data pipeline architecture and incorporating emerging technologies to optimize analytics platforms.
Skilled in enterprise AI integrations and advanced data modeling to enable various data consumption models (virtualization, reporting, etc.).
Comfortable operating in Agile environments, leading POCs, and collaborating cross-functionally with analytics, engineering, and business teams.