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Mid-level generalist Data Engineer with common Databricks/Snowflake/Python stack at a well-known employer increases competition.
Core data engineering skills transfer across industries despite healthcare experience being advantageous.
Explicit 3+ years plus mandatory Databricks, Snowflake and Python requirements make screening strict.
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Design, develop, and maintain scalable ETL/ELT pipelines and enterprise data workflows using Databricks and Snowflake.
Develop Python-based automation and data processing solutions; implement workflow orchestration, scheduling, and monitoring for real-time and batch data processing.
Collaborate with analytics, AI/ML, and reporting teams to ensure data quality, governance, security, performance optimization, and support data-driven decision-making.
3+ years of IT experience with a Bachelor's degree in Engineering, MCA, or MSc.
Strong experience with Databricks, Snowflake, Python programming, SQL, and data modeling.
Experience building ETL/ELT pipelines, workflow orchestration, and understanding of distributed data processing and cloud-based data engineering architectures.
Knowledge of APIs, automation frameworks, integration patterns, and familiarity with AI agents, intelligent orchestration, or automation frameworks.
Experienced in building and optimizing large-scale data engineering solutions within enterprise or regulated environments, preferably healthcare.
Skilled at collaborating in Agile teams, with strong problem-solving, debugging, and analytical capabilities.
Strategically aligns with innovation initiatives involving AI agents, intelligent automation, and continuous improvement in data platforms.