Snowflake‑Data Engineer - Delivery Manager

Job Purpose

We are seeking a highly skilled and Snowflake‑certified Data Engineer to independently design, build, and optimize scalable data solutions across the enterprise. The ideal candidate will have deep hands-on expertise in

Snowflake architecture, data modeling, and end‑to‑end pipeline development, along with a strong understanding of cloud data ecosystems, API integration, and enterprise data platforms. This individual

contributor role requires a self-driven engineer capable of owning complex data engineering initiatives end‑to‑end while ensuring performance, reliability, and alignment with business needs.

Key Responsibilities ◼ Independently design and implement Snowflake databases, schemas, warehouses, RBAC, and workload

management. ◼ Configure and optimize Snowpipe, Streams, Tasks, Materialized Views, Clustering, and Time Travel.

◼ Perform performance tuning and troubleshoot issues directly from the Snowflake portal. ◼ Design robust dimensional and normalized data models aligned with financial domain needs.

◼ Architect and implement Medallion (Bronze–Silver–Gold) data layers for scalable pipelines. ◼ Ensure data quality, governance, and secure access patterns.

◼ Build and manage end-to-end pipelines using:

• dbt for transformations
• Python for automation
• Airflow/ADF for orchestration

◼ Implement and maintain CI/CD workflows, code reviews, and automated deployment processes. ◼ Consume REST/SOAP APIs for data ingestion and integration.

◼ Connect Snowflake with enterprise systems and datasets (Salesforce, SAP, CRM/ERP, cloud services, IDP, etc). ◼ Integrate Snowflake with cloud-native services for ingestion, compute, and storage.

◼ Maintain high-performance, cost-efficient cloud data operations. ◼ Take complete ownership of design, development, deployment, and support with minimal oversight.

◼ Work directly with architects, business analysts, and stakeholders to translate requirements into solutions. ◼ Produce high-quality documentation, reusable components, and engineering best practices.

Key competencies ◼ Candidates should have a B.E./B.Tech/MCA/MBA in Information Systems, Computer Science or a related field

◼ 10–12 years of hands-on data engineering experience, including a minimum of 6 years dedicated to Snowflake. ◼ Advanced expertise in Snowflake architecture, implementation, administration, optimization, and troubleshooting.

◼ Experience with Snowflake Data Sharing and Snowflake Marketplace for accessing, integrating, and managing third‑party and shared datasets.

◼ Strong knowledge of data modeling and Medallion Architecture. ◼ Proficiency in SQL, Python, and cloud ecosystem workflows.

◼ Hands-on experience with dbt, Airflow, Azure Data Factory (ADF), or similar orchestration tools. ◼ Experience integrating REST/SOAP APIs and connecting Snowflake with enterprise platforms (CRM/ERP/SaaS

systems). ◼ Strong exposure to Azure or AWS cloud data services.

◼ Experience working in the financial domain (preferred but not mandatory). ◼ Familiarity with CI/CD, Git workflows, automated deployments, and DevOps best practices.

◼ Strong problem-solving skills, with ability to independently debug and resolve platform issues using Snowflake portal/console.

◼ Excellent communication skills, self-driven attitude, and ability to work independently with minimal supervision. ◼ Snowflake Certification (e.g., SnowPro Core or Advanced Data Engineer).