
Chief Data Architect
2 weeks ago
Unlocking Data Potential
We partner with organizations to drive informed decision-making, optimize infrastructure, and empower transformative insights.
- Migrating data warehousing and ETL processes from legacy systems to cloud environments enables efficiency and scalability. Leveraging Snowflake and dbt ensures seamless integration and streamlined operations.
- Designing highly reliable ETL/ELT pipelines within the new Snowflake environment optimizes SQL and workflows for performance and cost-efficiency.
- Establishing robust data quality, governance, and security standards within the new platform involves collaboration with stakeholders to translate data requirements into technical solutions.
- Developing best practices for data modeling, CI/CD, and version control using Git is crucial for mentoring junior engineers and contributing to continuous improvement.
- Troubleshooting and resolving complex data integration and data warehouse performance issues ensures seamless data flow.
Qualifications:
- A minimum of 5-10 years of experience in data engineering or a related field.
- Deep expertise in migrating data platforms from on-premises systems to cloud environments (AWS, Azure, or GCP) is essential.
- Mandatory hands-on experience with Teradata, Informatica, and Snowflake data warehousing is required.
- Expert-level proficiency in Snowflake, including performance tuning and platform administration, is necessary.
- Strong experience with dbt for data transformation, testing, and documentation is essential.
- Exceptional proficiency in SQL and at least one programming language (Python preferred) is required.
- Experience with cloud services and setting up data ingestion from various sources is beneficial.
- Excellent analytical, problem-solving, and communication skills are crucial.
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