Data engineer

About the Role

We are looking for a Data Engineer with 3–5 years of experience to build and maintain data pipelines, Snowflake integrations, and data platforms while supporting the administration, performance, security, and reliability of our database environments.

The ideal candidate should have strong SQL and RDBMS fundamentals, hands-on Snowflake experience, and the ability to work across relational and No SQL databases.

Key Responsibilities

Data Engineering & Snowflake

Design, develop, and maintain data pipelines and ETL/ELT processes using Snowflake. Develop complex SQL queries, transformations, views, stored procedures, tasks, and streams. Build incremental data ingestion and data synchronization pipelines. Implement and maintain Snowflake integrations with external applications, cloud storage, and data sources. Work with stages, file formats, COPY, Snowpipe, storage integrations, and connectors. Monitor and troubleshoot data pipelines and resolve data quality and processing issues. Optimize Snowflake queries and workloads for performance, scalability, and cost. Support data modeling and schema design for analytical workloads.

Database Operations

Manage and maintain databases across RDBMS and No SQL environments. Perform database administration activities including user/role management, access control, security, monitoring, maintenance, and troubleshooting. Implement and maintain RBAC and least-privilege access across database platforms. Monitor database health, performance, storage, and resource utilization. Perform query and database performance tuning and identify optimization opportunities. Support backup, recovery, disaster recovery, and database maintenance activities. Troubleshoot production database issues and participate in root-cause analysis and incident resolution. Maintain database standards, documentation, and operational procedures.

Required Skills & Experience

3–5 years of experience in Data Engineering or a similar role. Strong hands-on experience with Snowflake. Proficient in SQL, including complex queries, data transformation, and query optimization. Strong understanding of RDBMS and No SQL database concepts. Hands-on experience with databases such as Postgre SQL, Dynamo DB, or similar technologies. Experience with Snowflake Streams, Tasks, Stages, Snowpipe, Stored Procedures, Views, and Data Loading. Experience building and troubleshooting ETL/ELT data pipelines. Good understanding of database performance tuning, indexing, partitioning, and query optimization. Experience with database users, roles, permissions, and RBAC. Understanding of database security, monitoring, backup, and recovery concepts. Experience with Python or scripting for data engineering and automation. Strong troubleshooting and problem-solving skills.

Good to Have

Knowledge of Click House or other analytical databases. Experience with AWS cloud services and cloud-based data platforms. Experience working with B2 B Saa S / Mar Tech data platforms.