Snowflake Data Engineer- Consultant at KPMG India

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

10 Aug, 26

Salary

0.0

Posted On

12 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Snowflake, Python, SQL, AWS, Data Modeling, ETL/ELT, Cortex AI, Data Warehousing, CI/CD, RBAC, Agentic Development, Data Visualization, Airflow, dbt, Snowpipe, Stored Procedures

Industry

Business Consulting and Services

Description

Designation Consultant Reporting to Manas Yetirajam Role type Snowflake Engineer Employment type Full-time Job Requirements Mandatory Skills * Bachelor’s degree in computer science, Data Science, engineering, mathematics, information systems, or a related technical discipline * 5+ years of relevant experience in data engineering roles * Detailed knowledge of data warehouse technical architectures, data modelling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding * Proficient in at least one or more programming languages: Java, Python, Ruby, Scala * Experienced with AWS services such as Redshift, S3, EC2, Lambda, Athena, EMR, AWS Glue, Datapipeline. * Exposure to data visualization and reporting with tools such as Amazon QuickSight, Metabase, Tableau, or similar software * Experience building metrics deck and dashboards for KPIs including the underlying data models. * Understand how to design, implement, and maintain a platform providing secured access to large datasets Primary Roles and Responsibilities As a Snowflake Data Engineer, you will design, build, and operate enterprise-grade data platforms on Snowflake. You will develop secure, governed, and cost-efficient data pipelines and models; enable analytics and AI/ML use cases using Snowflake core services and Snowflake Cortex AI; and partner with business stakeholders to deliver reliable, high-performance data capabilities. The role spans ingestion, transformation, data architecture, performance tuning, security, and observability—anchored in Python, SQL, and agentic development patterns. Preferred Skills * Education: Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Information Systems, or related technical discipline * Experience: 5+ years in data engineering with modern data warehousing; 3+ years hands-on with Snowflake (enterprise implementations) * Technical proficiency: * Strong Python and SQL (query optimization, UDFs, stored procedures) * Background in agentic development (designing LLM/agent workflows, orchestration, prompt engineering, tool/function calling, evaluation) * Data architecture/platform enablement with Snowflake (account/org setup, multi-DB design, RBAC, data sharing, governance) * Data warehouse architectures, dimensional/data vault modeling, ETL/ELT patterns, and CI/CD for data * Building metrics layers and KPI dashboards with underlying semantic/data models Snowflake platform skills: * Core: Warehouses, Databases/Schemas, Stages, Snowpipe, Tasks, Streams, External Tables * Performance and cost optimization (clustering, micro-partitions, query profiling, warehouse sizing, workload isolation) * Security and governance: RBAC, masking/row-access policies, network policies, platform observability, data lineage * Integration with cloud object stores and identity (e.g., AWS S3 + IAM roles, or Azure/GCP equivalents) * Data visualization exposure with tools such as Tableau, QuickSight, Power BI, or Metabase * Ability to design, implement, and maintain secure access to large datasets at scale * Primary Roles and Responsibilities * Architect and operationalize Snowflake environments (multi-account/org patterns, RBAC, security controls, data sharing/clean rooms) * Define data models (dimensional/vault), data contracts, and semantic layers aligned to business KPIs * Data Engineering and Automation * Build resilient ELT workflows using Snowflake-native features (Snowpipe, Streams & Tasks) and orchestrators (Airflow, dbt, etc.) * Develop high-performance SQL transformations, stored procedures (Snowflake Scripting/Python), and UDFs * Implement CI/CD for data (versioning, testing, data quality checks, Dev/Test/Prod promotion) * Performance, Reliability, and Cost Management * Tune queries and storage, optimize clustering and warehouse configurations, and set workload isolation/SLOs * Establish monitoring, alerting, and cost governance; drive continuous improvements in efficiency * Security, Governance, and Compliance * Enforce data privacy and access controls (masking, row access, object dependencies), and document lineage * Implement data sharing and collaboration with strong governance, policies, and auditability * AI/ML and Advanced Analytics on Snowflake * Leverage Snowflake Cortex AI to analyze unstructured data and build LLM-powered apps using SQL/Python * Implement and operationalize: * Snowflake Intelligence for natural language Q&A across structured/unstructured data (e.g., PDFs, Salesforce) * Cortex Search for semantic search over enterprise documents * Cortex Analyst for conversational text-to-SQL over structured data * Document AI for document and image extraction * Cortex Code to accelerate development for data engineering and analytics * Ensure all AI features run within Snowflake’s secure, governed perimeter with role-based access control * Stakeholder Partnership * Collaborate with business owners to translate requirements into data solutions and analyses * Deliver metrics decks and dashboards; perform root-cause analysis and develop business cases for improvements Other Information Number of interview rounds 2 Mode of interview Virtual Job location Bangalore/Pune/Gurgaon Clean room policy (specific to business) NA Culture * Corporate Social Responsibility programs * Maternity and paternity leave * Opportunities to network and connect * Discounts on products and services Note: Benefits/Perks listed above may vary depending on the nature of your employment with KPMG and the country where you work.

Responsibilities

Design, build, and operate enterprise-grade data platforms on Snowflake, focusing on secure and cost-efficient data pipelines. Implement AI/ML use cases using Snowflake Cortex AI and partner with stakeholders to deliver high-performance data capabilities.