About the Role :
We are seeking a highly skilled Senior Data Engineer with strong expertise in Snowflake, SQL, and Python to design, build, and optimize our data ecosystem. You will play a critical role in creating scalable data pipelines, ensuring high data quality, and supporting analytics and AI / ML initiatives across the organization. This position is ideal for someone who enjoys solving complex data problems and building enterprise-grade data platforms.
Key Responsibilities :
- Design, build, and maintain scalable ETL / ELT pipelines using Snowflake, Python, and related tools.
- Automate data ingestion from multiple structured and unstructured sources (APIs, databases, cloud storage, etc.).
- Implement pipeline monitoring, error handling, retry logic, and alerts.
- Develop and maintain Snowflake objects such as schemas, tables, views, streams, tasks, stages, and warehouses.
- Optimize Snowflake performance through warehouse sizing, clustering, micro-partitioning, and query tuning.
- Implement data sharing, secure views, role-based access models, and data governance practices.
- Write complex, high-performance SQL queries for data transformation and analytics.
- Design and implement data models (3NF, Star / Snowflake schema) that support BI and analytics use cases.
- Implement data quality frameworks, validation checks, and reconciliation processes.
- Use Python for data transformation, ingestion frameworks, API integration, and ETL automation.
- Build reusable components, libraries, and scripts for workflow orchestration.
- Set up continuous monitoring of pipelines, Snowflake performance, and data quality metrics.
- Ensure data privacy, compliance, and security using best practices (RBAC, masking policies, encryption).
- Troubleshoot complex data and performance problems.
- Partner with data analysts, BI developers, and data scientists to understand requirements and deliver reliable datasets.
- Collaborate with DevOps / Cloud teams on infrastructure provisioning, CI / CD, and deployment.
- Provide technical mentorship to junior engineers.
Required Skills & Experience :
5+ years of hands-on experience in Data Engineering, with at least 3+ years in Snowflake.Strong expertise in Snowflake SQL, Snowflake components, and performance tuning.Proficiency in Python for building scalable ETL / ELT workflows.Strong understanding of ETL processes, data integration patterns, and data warehousing concepts.Experience with data modeling (dimensional & relational).Knowledge of cloud platforms (AWS / Azure / GCP); familiarity with S3, Lambda, Databricks, or similar is a plus.Experience using workflow orchestration tools (Airflow, DBT, Prefect, etc.) is an advantage.(ref : hirist.tech)