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Tier-1 brand, popular data-engineer role, metro location, and broad skillset increase candidate competition.
Specialized data-platform skills required, yet broadly applicable across industries.
Explicit 8–10 years requirement plus mandatory Snowflake/Databricks/Spark/cloud skills makes filters strict.
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Design, build, and optimize scalable data pipelines and platforms supporting analytics, reporting, and downstream applications.
Ensure data quality, governance, lineage, and implement data solutions on cloud platforms like Snowflake and Databricks following architectural standards.
Lead cross-team initiatives, mentor junior engineers, and contribute to developing internal data engineering tools and frameworks.
7-10 years of experience in Data Engineering or related roles.
Bachelor's Degree or equivalent combination of coursework and experience.
Proficiency in advanced SQL, Python (preferred), distributed computing frameworks (e.g., Apache Spark), and cloud data platforms (AWS, GCP, Azure).
Experience with Snowflake, Databricks, data pipeline design, data modeling, data observability, and workflow orchestration tools (e.g., dbt, Airflow).
Experienced in leading complex, high-impact data engineering projects with cross-team collaboration.
Skilled in cloud-based data warehousing, data quality and validation frameworks, and CI/CD deployment processes.
Able to mentor junior engineers and shape internal data engineering best practices and tool development.