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:
o dbt for transformations
o Python for automation
o 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 (Salesforce, SAP, CRM/ERP, cloud services).
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).
Snowflake, Data Engineer, Architect, DBT, SQL, Python,Airflow