Hakkōda, an IBM Company, is seeking a Sr. Consultant, Data Engineer to join their team of experts. The role involves designing and developing Snowflake Data Cloud solutions, leading technical teams, and optimizing data systems for customer projects.
Responsibilities:
- Work in the design and development of Snowflake Data Cloud solutions
- Develop database architectures and data warehouses
- Ensure optimal data delivery architecture is consistent throughout ongoing customer projects
- Lead technical teams
Requirements:
- Bachelor's degree in engineering, computer science or equivalent area
- Expertise in evaluating, selecting, and integrating ingestion technologies to solve complex data challenges
- Leadership in architectural decisions for high-throughput data ingestion frameworks, including real-time data processing and analytics
- Mentorship of junior engineers in best practices for data ingestion, performance tuning, and troubleshooting
- 5+yrs in related technical roles, data management, database development, ETL, Data Warehouses and pipelines
- Experience designing and developing data warehouses (Teradata, Oracle Exadata, Netezza, SQL Server, Spark)
- Experience building ETL / ELT ingestion pipelines with tools like DataStage, Informatica, Matillion
- SQL scripting
- Cloud experience on AWS (Azure, GCP are nice to have as well)
- Python Scripting, Scala is required
- Ability to prepare reports and present to internal and customer stakeholders
- Track record of sound problem solving skills and action oriented mindset
- Strong interpersonal skills including assertiveness and ability to build strong client relationships
- Ability to work in Agile teams
- Experience hiring, developing and managing a technical team
- Master's Degree
- Advanced Snowflake Platform Knowledge: Experience with advanced Snowflake features, including data sharing, data pipelines, and data security. Ability to design and implement complex data and AI usecases on Snowflake platforms
- Cloud Architecture Expertise: Experience with designing and implementing scalable and secure cloud architectures for data and AI applications. Knowledge of cloud migration, deployment, and management best practices
- Data Engineering Best Practices: Experience with implementing data engineering best practices, including data modeling, data warehousing, and data governance. Ability to optimize data and AI solutions for performance and scalability