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Data Engineer with SQL and Snowflake
N Consulting Ltd
City of Edinburgh
Hybrid
GBP 60,000 - 80,000
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Job summary
An innovative firm is seeking a Data Engineer with expertise in SQL and Snowflake to join their dynamic team. In this role, you will design and implement scalable data pipelines, leveraging your strong experience in ETL processes and cloud platforms, particularly AWS. Your skills in SQL Server and data warehousing principles will be crucial in optimizing data loading and transformation processes. This position offers a hybrid work environment, allowing you to balance your professional and personal life while contributing to exciting projects that drive data-driven decisions. If you're passionate about data engineering and looking for a new challenge, this opportunity is perfect for you.
Qualifications
- Proven experience in SQL Server with strong skills in T-SQL and query optimization.
- Strong experience in Snowflake architecture and ETL processes.
Responsibilities
- Design and implement scalable data pipelines using SQL and Snowflake.
- Optimize data loading and transformation processes in a cloud environment.
Skills
SQL Server
Snowflake
ETL Processes
AWS Cloud Services
Data Warehousing Principles
Data Modeling
Version Control (GitLab)
Tools
Informatica PowerCenter
AutoSys
Airflow
SQL Server Agent
Job description
Role :Data Engineer with SQL and Snowflake
Duration: 6 months
Location: Edinburgh(Hybrid)
Required Skills and Qualifications:
- Proven experience working with SQL Server (e.g., T-SQL, Stored Procedures, Indexing, Query Optimization, System Catalog Views).
- Strong experience in Snowflake architecture, including data loading, transformation, and performance tuning.
- Proficient in ETL processes using tools such as Informatica PowerCenter and BDM, AutoSys, Airflow, and SQL Server Agent.
- Experience with cloud platforms preferably AWS.
- Strong knowledge of AWS cloud services, including EMR, RDS Postgres, Redshift Athena, S3, and IAM.
- Solid understanding of data warehousing principles and best practices.
- Strong proficiency in SQL for data manipulation, reporting, and optimization.
- Knowledge of data modeling and schema design.
- Experience working with large, complex datasets and implementing scalable data pipelines.
- Familiarity with version control tools such as GitLab.
- Experience with data integration, data governance, and security best practices.
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