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Medium competition: recognized global brand but senior, specialized data engineering reduces applicant pool.
Medium: core data engineering skills transfer across industries, though Snowflake and retail insights add domain preference.
High: explicit 10+ years requirement and strict data platform, Snowflake, cloud, and IaC skill mandates.
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Design and develop scalable, reliable data pipelines and cloud-native data platforms using Python, SQL, Snowflake, and cloud technologies.
Lead architecture decisions and optimize data solutions for performance, cost, and reliability including AI/ML workflow enablement.
Provide technical leadership and mentoring across engineering teams, and drive CI/CD automation and data governance practices.
10+ years of experience in Data Engineering.
Strong proficiency in Python, SQL, and Snowflake or equivalent cloud data warehouse technology.
Experience with cloud platforms: preferably Microsoft Azure, also AWS or GCP.
Hands-on knowledge of CI/CD pipelines, Infrastructure as Code (Terraform, CloudFormation), and DevOps tools.
Experienced in building and optimizing enterprise-scale data platforms with cloud-native architectures and data governance.
Technical leader capable of driving architecture strategy, mentoring senior engineers, and collaborating with diverse stakeholders.
Familiarity with AI/ML pipelines, Generative AI, LLM integrations, and modern data technologies like Spark, Kafka, and Data Mesh principles.