Job highlights

- Candidates must have hands-on experience with Snowflakes core functionalities,including designing database schemas,efficiently loading data (using features like Snowpipe or the COPY into command),optimizing query performance,and managing user roles and access within Snowflake
- Experience: 5-8 years of experience in data engineering,DevOps,or a related technical field

Snowflake Migration Leadership: Led all phases of migration including but not limited to planning to optimization, ensuring a smooth transition with data integrity and minimal service disruption Data Pipeline Development & Orchestration:

Lead the design and implementation of scalable ETL/data pipelines using Python and Luigi for data processing

Ensure efficient data processing for high-volume clickstream, demographics, and business data

Cloud Infrastructure Management

Configure, deploy, and maintain AWS infrastructure, primarily AWS EC2, S3, RDS, and EMR, to ensure scalability, availability, and security

Support data storage and retrieval workflows using S3 and SQL-based storage solutions

Legacy System Maintenance & Upgrade Initiatives:

Oversee legacy framework maintenance, identify improvement areas, and propose cloud migration or modernization plans

Coordinate infrastructure changes with stakeholders to align with business needs and budget constraints

Monitoring & Troubleshooting:

Develop monitoring solutions to track system health, performance, and pipeline accuracy

Set up alerts and dashboards for proactive issue detection and collaborate with cross-functional teams to resolve critical issues

Documentation & Knowledge Sharing:

Document workflows, troubleshooting procedures, and code for system transparency and continuity





Provide mentoring and training to team members on best practices and technical skills

Minimum Qualifications

Experience: 5-8 years of experience in data engineering, DevOps, or a related technical field

Snowflake Expertise: 3+ years of hands-on experience on Snowflake

Candidates must have hands-on experience with Snowflakes core functionalities, including designing database schemas, efficiently loading data (using features like Snowpipe or the COPY into command), optimizing query performance, and managing user roles and access within Snowflake

Python: Strong Python skills for scripting migration processes, custom ETL, and API interactions with Snowflake

Programming & Scripting: Strong programming skills in Python and Linux Bash for automation and data workflows

Framework Proficiency: Hands-on experience with Luigi for orchestrating complex data workflows

Data Processing & Storage: Expertise in Hadoop ecosystem tools and managing SQL databases for data storage and query optimization

AWS Cloud Services: In-depth knowledge of AWS EC2, S3, RDS, and EMR to deploy and manage data solutions

Monitoring & Alerting Tools: Familiarity with monitoring solutions for real-time tracking and troubleshooting of data pipelines

Communication & Leadership: Proven ability to lead projects, communicate with stakeholders,



and guide junior team members

Additional Experience Desired

Migration Tools & Strategies: Experience with specific data integration and ETL tools like Fivetran or Matillion, which are often used for effective data loading and transformation into Snowflake, would be a significant advantage

Knowledge of custom scripting for migration is also valuable

Data Governance in Snowflake: Understanding how to apply data governance, security protocols, and compliance frameworks within Snowflake is highly desirable

This includes knowledge of features like dynamic data masking, row-access policies, and external tokenization

CI/CD for Data Pipelines: Experience with CI/CD practices specifically for data pipelines, including automated testing and deployment of Snowflake objects (eg, using tools like dbt), would be a plus

Security Practices: Understanding of data security practices, data governance, and compliance for secure data processing

Automation & CI/CD: Familiarity with CI/CD tools to support automation of deployment and testing

Big Data Technologies: Knowledge of big data processing tools like Spark, Hive, or related AWS services

Advanced Analytics: Background in analytics or data science to contribute to more data-driven decision-making

Cross-Functional Collaboration: Experience collaborating with non-technical teams on business goals and technical solutions

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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