Snowflake Developer

Job Title: Snowflake Developer
Experience: 1-4 Years
Location: Hyderabad
Department: Data Engineering / IT
Job Type: Full Time

Key Responsibilities

• Develop and maintain Snowflake-based data pipelines, transformations, and database objects across ingestion, staging, and curated layers.
• Implement data solutions based on project requirements and technical direction provided by Leads and Architects.
• Build and support ETL/ELT workflows using tools such as dbt, Airflow, Matillion,Informatica, Fivetran, ADF, Glue, or custom Python-based frameworks.
• Work with structured,semi-structured, API-sourced, and file-based data and prepare it for downstream analytics, BI, AI/ML, and operational use cases.
• Design and optimize SQL transformations, loading processes, and Snowflake objects for performance, scalability, maintainability, and cost efficiency.
• Support implementation of medallion-style architecture patterns such as RAW/STAGING/CURATED or Bronze/Silver/Gold.
• Troubleshoot pipeline failures, ingestion issues, schema drift, transformation defects, data quality issues, and performance bottlenecks.
• Perform data validation, reconciliation, and quality checks to support reliable delivery and accurate downstream reporting.
• Independently research unfamiliar source systems, APIs, connectors, ingestion patterns, and implementation approaches needed for assigned work.
• Use modern AI-assisted engineering tools such as LLMs and coding assistants productively and responsibly to accelerate technical research, prototyping,troubleshooting, documentation, and development tasks.
• Validate, test, and refine AI-assisted outputs before applying them to project delivery.
• Compare implementation options and surface practical recommendations, assumptions, dependencies,and risks to Leads and Architects.
• Collaborate with Leads, Architects, BI developers, analysts, QA teams, and client stakeholders to clarify requirements and resolve technical issues.
• Support CI/CD, code migration, version control, and deployment processes across development,test, and production environments.
• Contribute to technical documentation including source-to-target mappings, pipeline logic,operational run notes, deployment notes, and implementation assumptions.
• Follow best practices for secure development, role-based access control, governed data handling,and operational reliability within Snowflake environments.

Required Skills & Qualifications

• 1-4 years of experience in data engineering, ELT/ETL development, or cloud data platform implementation.
• Hands-on experience working with Snowflake in development or project delivery environments.
• Strong SQL skills and solid understanding of relational data modeling, warehouse concepts, and transformation logic.
• Experience building and supporting data pipelines using one or more ETL/ELT or orchestration tools such as dbt, Airflow, Matillion, Informatica, Fivetran, ADF, Glue, or similar platforms.
• Working knowledge of Python for data ingestion, automation, scripting, or transformation support.
• Familiarity with at least one major cloud platform such as AWS, Azure, or GCP.
• Experience handling files, APIs, and semi-structured data formats such as JSON, CSV, XML, or similar.
• Strong troubleshooting and debugging skills across ingestion, transformation, and deployment workflows.
• Strong problem-solving skills with the ability to independently research technical issues and move implementation tasks forward with limited supervision.
• Demonstrated ability to use modern AI-assisted engineering tools productively for technical research, prototyping, troubleshooting, and documentation.
• Ability to critically assess AI-generated suggestions and convert them into reliable,production-appropriate solutions.
• Familiarity with Git,version control, and deployment practices in data engineering environments.
• Good communication skills and the ability to work effectively within delivery teams.

Preferred Qualifications

• Experience working in a consulting, services, or multi-client delivery environment.
• Exposure to medallion architecture and layered data platform design patterns.
• Familiarity with Snowflake security concepts, role-based access control, and cost/performance optimization basics.
• Exposure to BI, semantic modeling, reverse ETL, AI/ML-oriented downstream use cases, or analytics engineering practices.
• Experience using tools such as ChatGPT, Claude, GitHub Copilot, or similar AI-assisted development platforms as part of engineering workflows.
• Exposure to near-real-time or CDC-based ingestion patterns.
• Snowflake certification such as SnowPro Core, Advanced, cloud/tools certifications.