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Mid-level popular Data Engineer role with broad tech requirements and metro hybrid location increases applicant competition.
Core data engineering skills are widely transferable across industries, lowering background sensitivity.
Explicit 3+ year requirement plus mandatory Databricks, Snowflake, and Python skills enforce moderate filtering.
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Design, develop, and maintain scalable ETL/ELT data pipelines and workflows using Databricks, Snowflake, and Python.
Implement workflow orchestration, scheduling, dependency management, and monitor data processing solutions for both real-time and batch use cases.
Collaborate with analytics, AI/ML, and reporting teams to enable data-driven decision-making while ensuring data quality, governance, security, and performance optimization.
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.
Proven skills in building ETL/ELT pipelines, distributed data processing, workflow orchestration, and cloud-based data engineering architectures.
Work Experience Required: Minimum 3 years in IT roles relevant to data engineering.
Experienced in designing and optimizing data engineering solutions within enterprise or regulated healthcare environments preferred but not mandatory.
Comfortable working in Agile, cross-functional teams supporting analytics, AI/ML, and reporting workflows.
Skilled in automation frameworks, API integration, performance tuning, and continuous improvement initiatives with hands-on exposure to Apache Spark/PySpark and DevOps/CI/CD practices.