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Snowflake, Python
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Job Description
Technology->Data on Cloud-DataStore->Snowflake Technology->->Python
Key Responsibilities: Data Platform & Solution Delivery - Lead the design and implementation of Snowflake-based data warehouse/lakehouse solutions aligned to business needs. - Build and optimize ELT/ETL pipelines using Python and dbt to deliver curated, analytics-ready datasets. - Develop and maintain Snowflake objects (schemas, tables, views, stages) and implement efficient data modeling patterns. - Drive performance tuning across Snowflake (warehouse sizing, clustering, query optimization) and transformation layers. Engineering Excellence & Reliability - Establish coding standards, reusable frameworks, and best practices for Python and dbt development. - Implement data quality checks, automated testing, and monitoring to ensure reliable and accurate data delivery. - Ensure secure data access patterns and support governance practices such as role-based access and auditing. Leadership & Collaboration - Mentor engineers, conduct code reviews, and guide the team on design decisions and implementation approaches. - Partner with stakeholders to translate requirements into technical designs, delivery plans, and measurable outcomes. - Support release planning, incident triage, and continuous improvements to reduce operational overhead. Minimum Qualifications: - BTECH, MTECH, MCA, MSC (or equivalent) in Computer Science, Engineering, or a related field. - 6–8 years of overall experience in data engineering / data platform development. - 6+ years of hands-on experience with Snowflake, including data modeling, performance tuning, and administration fundamentals. - 6+ years of hands-on experience with Python for building data pipelines, automation, and integrations. - Strong SQL skills and experience building reliable, maintainable transformations and datasets. - Proven experience delivering production-grade data solutions with attention to scalability, reliability, and maintainability.
Preferred Qualifications: - Strong hands-on experience with dbt (models, macros, tests, documentation, and deployment practices). - Experience designing modular transformation layers (staging/intermediate/marts) and implementing robust data quality frameworks. - Familiarity with orchestration and scheduling patterns for pipelines and transformations. - Experience with CI/CD practices for data engineering (version control workflows, automated testing, and release management). - Demonstrated ability to lead technical discussions, influence architecture decisions, and mentor team members effectively.
Key Responsibilities: Data Platform & Solution Delivery - Lead the design and implementation of Snowflake-based data warehouse/lakehouse solutions aligned to business needs. - Build and optimize ELT/ETL pipelines using Python and dbt to deliver curated, analytics-ready datasets. - Develop and maintain Snowflake objects (schemas, tables, views, stages) and implement efficient data modeling patterns. - Drive performance tuning across Snowflake (warehouse sizing, clustering, query optimization) and transformation layers. Engineering Excellence & Reliability - Establish coding standards, reusable frameworks, and best practices for Python and dbt development. - Implement data quality checks, automated testing, and monitoring to ensure reliable and accurate data delivery. - Ensure secure data access patterns and support governance practices such as role-based access and auditing. Leadership & Collaboration - Mentor engineers, conduct code reviews, and guide the team on design decisions and implementation approaches. - Partner with stakeholders to translate requirements into technical designs, delivery plans, and measurable outcomes. - Support release planning, incident triage, and continuous improvements to reduce operational overhead. Minimum Qualifications: - BTECH, MTECH, MCA, MSC (or equivalent) in Computer Science, Engineering, or a related field. - 6–8 years of overall experience in data engineering / data platform development. - 6+ years of hands-on experience with Snowflake, including data modeling, performance tuning, and administration fundamentals. - 6+ years of hands-on experience with Python for building data pipelines, automation, and integrations. - Strong SQL skills and experience building reliable, maintainable transformations and datasets. - Proven experience delivering production-grade data solutions with attention to scalability, reliability, and maintainability.
Preferred Qualifications: - Strong hands-on experience with dbt (models, macros, tests, documentation, and deployment practices). - Experience designing modular transformation layers (staging/intermediate/marts) and implementing robust data quality frameworks. - Familiarity with orchestration and scheduling patterns for pipelines and transformations. - Experience with CI/CD practices for data engineering (version control workflows, automated testing, and release management). - Demonstrated ability to lead technical discussions, influence architecture decisions, and mentor team members effectively.
More Info
Key Skills
Data Quality Checks
Orchestration and Scheduling
CI/CD
Role-based Access
About Company
Skills:
Docker, FastAPI, Datadog, Python, LangChain, Vector Databases, Uvicorn
Skills:
Django, Numpy, Pandas, Flask, Data Structures And Algorithms, Version Control, Python, Testing, Software Development Best Practices, Scikit-learn
Skills:
S3, Data Modeling, Power Bi, Tableau, Sql, Python, AWS, LangChain, LangGraph, Vector Databases, semantic search, Glue, Knowledge Graphs
Skills:
bedrock , S3, Lambda, ECS, Aws Cloud, Python, Prompt engineering, OpenSearch, EKS, Snowflake Data Cloud, Agentic AI concepts, Strong SQL
Stand up Databricks and Snowflake platforms on AWS infrastructure. Career Arch Job code Overview antt data north america
Skills:
snowflake , Jenkins, Terraform, PowerShell, Gitlab, Databricks, Bash, Python, AWS, Azure DevOps, GitHub Actions