Sr. Data Engineer
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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level generalist data engineer role with common Azure/Snowflake skills attracts many applicants.
Technical data engineering skills are transferable across industries despite healthcare-specific domain context.
Explicit 5–8 years requirement plus mandatory Azure, Snowflake, Databricks, Python, and SQL increases strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain end-to-end data pipelines and ETL/ELT workflows using Python, SQL, Azure Data Factory, Snowflake, Databricks, and related technologies.
Build scalable data ingestion frameworks for structured, semi-structured, and unstructured data from multiple sources including files, APIs, and enterprise applications.
Drive improvements in data architecture, performance tuning, optimization, monitor and troubleshoot data pipelines, and deliver reports using SQL and Power BI.
Minimum Requirements
5–8 years of professional experience in Data Engineering.
Strong programming skills in Python for ETL, data ingestion, and transformation.
Hands-on expertise in Azure Cloud services including Azure Data Factory, Databricks, Azure Storage, Azure SQL, and Synapse.
Strong knowledge of Power BI, advanced analytics, SQL including complex queries and performance tuning, and experience with Snowflake data warehouse design.
Ideal Candidate Profile
Experienced working with structured, semi-structured (JSON, Parquet), and unstructured data in enterprise environments.
Familiar with Agile methodologies, version control (Git), CI/CD practices, and Azure DevOps workflows.
Experience or exposure to AI/ML concepts and solutions, particularly data preparation for AI use cases or AI-powered document extraction is a plus.