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Mid-level generalist data-engineer in a metro location with common skillset increases competition.
Strong transferable data-engineering skills, though Snowflake and GenAI experience raise domain specificity.
Explicit 3+ years, SQL/cloud/Snowflake and distributed systems requirements enforce moderate filtering.
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Design and build scalable backend systems and data access layers for data-intensive, analytics-driven applications.
Develop and optimize data workflows on platforms like Snowflake, ensuring high performance and efficient querying of large datasets.
Leverage GenAI/LLM capabilities to build intelligent data products and collaborate with stakeholders to translate requirements into technical solutions.
3+ years of experience in backend engineering building scalable, reliable, and high-performance production systems.
Strong proficiency in Python, Java, or similar language, with solid data structures and algorithms knowledge.
Experience with SQL including query optimization and working with large-scale datasets; hands-on experience with relational/analytical databases such as Snowflake, Redshift, PostgreSQL, MySQL.
Bachelor’s Degree in Computer Science or equivalent.
Experienced in distributed systems with knowledge of scalability, fault tolerance, and system design to own end-to-end backend architecture.
Familiarity with cloud platforms (AWS/GCP/Azure) and modern data infrastructure, including data modeling and schema design for analytics use cases.
Interest or exposure to GenAI/LLM applications, real-time processing systems (Kafka, Kinesis), and data engineering tooling for evolving data platforms.