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Popular data-engineer role, metro location, and broad Snowflake/Python/AWS skill set increase applicant competition.
Skills (Snowflake, Python, SQL, cloud) are highly transferable across industries despite finance preference.
Multiple explicit years and mandatory Snowflake, Python, SQL, and AWS requirements increase screening strictness.
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Design, develop, and support scalable data pipelines and automated workflows using Snowflake, Python, SQL, and AWS cloud services integrating cloud and on-premises data sources.
Ensure data transformation, validation, reconciliation, quality, security, performance, and cost-efficiency of data solutions supporting analytics and business requirements.
Collaborate with cross-functional distributed teams following Agile methodologies to troubleshoot, optimize, document, and improve data engineering processes and architectures.
8+ years of professional experience in data engineering or related technology roles.
5+ years experience integrating data between cloud and on-premises databases.
3+ years hands-on experience with Snowflake and Python programming including shell scripting.
Bachelor's degree in Computer Science, IT, Data Engineering or related field; equivalent professional experience considered.
Proven ability to build and maintain end-to-end data pipelines and data architectures in hybrid cloud environments using Snowflake, Python, SQL, and AWS services.
Effective participant in Agile distributed teams collaborating with technical and business stakeholders to deliver scalable, secure, and maintainable data solutions.
Strong experience optimizing Snowflake workloads including performance tuning and cost-efficient cloud resource utilization.