Senior Data Engineer

Role :SME-Snowflake

Role Overview

We are looking for a Snowflake Subject Matter Expert responsible for designing, implementing, optimizing, and governing enterprise-scale data platforms on Snowflake. Provide technical leadership for data modernization initiatives, SAP data integration, AI-ready data foundations, and best practices around performance, security, scalability, and cost optimization.

Responsibilities

• Serve as the primary Snowflake SME for enterprise data platform initiatives and client engagements.
• Design and implement scalable data architectures leveraging Snowflake and at least one additional cloud data platform such as Databricks or Google BigQuery.
• Develop and maintain Snowflake data models, schemas, data pipelines, and data-sharing architectures.
• Drive Snowflake performance optimization, workload management, query tuning, and cost governance initiatives.
• Define and implement data governance, security, role-based access control (RBAC), masking policies, row-level security, and compliance frameworks within Snowflake.
• Lead SAP ECC/S4HANA data integration and migration programs into Snowflake-based cloud data platforms.
• Architect AI-ready data foundations to support advanced analytics, machine learning, Generative AI, and LLM-powered use cases.
• Enable Snowflake capabilities including Snowpark, Dynamic Tables, Streams & Tasks, Native Apps, Data Sharing, Marketplace, Cortex AI, and Iceberg Tables where applicable.
• Collaborate with business stakeholders, data engineers, analytics teams, and solution architects to translate business requirements into scalable Snowflake solutions.
• Establish Snowflake best practices, design standards, reusable frameworks, and governance models across projects.
• Mentor technical teams on Snowflake architecture, data engineering practices, and cloud-native development patterns.
• Evaluate new Snowflake features and recommend adoption strategies to improve platform capabilities.

Required Skills

Snowflake Expertise

• 12+ years of experience in Data Engineering/Data Warehousing with 5+ years of hands-on Snowflake experience.
• Deep expertise in Snowflake architecture, virtual warehouses, storage, compute optimization, data sharing, cloning, time travel, fail-safe, and multi-cluster environments.
• Strong experience with Snowflake security, governance, RBAC, masking policies, network policies, and data protection frameworks.
• Strong experience with at least one additional cloud data platform such as Databricks or Google BigQuery.
• Expertise in modern data lakehouse and data warehouse architectures.
• Experience with ELT/ETL frameworks, data ingestion, CDC, and real-time data processing.
• Proficiency in SQL, Python, Snowpark, Spark/PySpark, and cloud-native data services.
• Experience integrating data from SAP ECC, SAP S/4HANA, SAP BW, SAP BDC Connect, or SAP Datasphere into Snowflake.
• Understanding of supply chain, inventory, procurement, manufacturing, and logistics data domains is highly desirable.
• Experience enabling AI/ML workloads on Snowflake.
• Familiarity with Generative AI, LLM integration, vector databases, RAG architectures, and agentic AI workflows.
• Knowledge of Snowflake Cortex AI capabilities is preferred.

Soft Skills

• Strong stakeholder management and consulting skills.
• Excellent communication, presentation, and documentation abilities.
• Ability to lead technical discussions, architecture reviews, and client workshops.
• Experience mentoring and guiding engineering teams.

Preferred Certifications

• SnowPro Advanced: Architect
• SnowPro Core Certification
• Cloud certifications on Amazon Web Services, Google Cloud, or Microsoft Azure