Celtic Management Services
Job Description
Location: Galway , Ireland
Contract Duration : 1 years
Salary : To be Discussed over the call
Start Date : Live
A Data Warehouse Engineer is responsible for the design, development, and maintenance of data warehouses. A data warehouse is a large centralized repository that consolidates data from different sources, making it easier for organizations to analyze and make strategic decisions. Data Warehouse Engineers play a crucial role in ensuring that large volumes of data are organized, stored, and processed effectively.
Key Responsibilities:
Data Warehouse Design and Architecture: * Design the architecture of data warehouses to ensure they can handle large datasets, scale as needed, and integrate seamlessly with other systems.
* Create data models, schemas, and ETL (Extract, Transform, Load) pipelines that ensure data is structured properly for reporting and analysis.
ETL Development : * Develop and manage ETL processes to extract data from various sources (e.g., databases, APIs, files), transform it into a usable format, and load it into the data warehouse.
* Ensure that ETL processes are optimized for performance and handle data efficiently.
Data Integration : * Integrate data from various operational databases and external data sources into the data warehouse.
* Ensure that the data from different sources is consistent, accurate, and adheres to business rules.
Data Warehouse Maintenance: * Monitor the performance of the data warehouse, troubleshoot issues, and make improvements to ensure efficient storage and retrieval of data.
* Handle data backups, recovery, and security within the data warehouse environment.
Data Governance and Quality: * Ensure data governance policies are followed and that the data within the warehouse is of high quality, clean, and well-organized.
* Implement validation rules and processes to maintain the integrity and accuracy of the data.
Performance Optimization: * Optimize data warehouse performance through indexing, partitioning, and query optimization techniques.
* Ensure that data retrieval is fast and efficient, even with large datasets.
Collaboration with Stakeholders: * Work closely with data analysts, data scientists, and business intelligence teams to ensure that the data warehouse meets their needs for analytics and reporting.
* Collaborate with software engineers, database administrators, and other IT staff to ensure seamless integration with other systems.
Tool and Technology Expertise: * Proficiency in data warehousing tools like Amazon Redshift, Snowflake, Google BigQuery, Microsoft Azure Synapse, and traditional data warehouse solutions like Teradata and Oracle.
* Strong knowledge of ETL tools like Apache NiFi, Talend, Informatica, and programming languages like SQL, Python, and Scala.
Scalability and Performance Tuning: * Design systems that can scale with increasing data volumes, ensuring that the infrastructure can handle growth without performance degradation.
Skills Required:
Database Knowledge: Deep understanding of relational databases (e.g., SQL Server, Oracle, PostgreSQL) and NoSQL databases.
ETL Development: Expertise in ETL tools and technologies, as well as a strong ability to work with large-scale data integration tasks.
Data Modeling: Proficiency in designing data models (e.g., star schema, snowflake schema) to support efficient querying and reporting.
Programming: Strong programming skills, particularly in SQL and possibly in scripting languages like Python or Bash for automation.
Cloud Computing: Experience with cloud-based data warehouses (e.g., AWS Redshift, Google BigQuery, Snowflake).
Problem Solving: Ability to troubleshoot complex data issues and optimize the data pipeline for performance.
In summary, a Data Warehouse Engineer plays a critical role in ensuring that organizations can effectively store, manage, and analyze large amounts of data. Their work is foundational to business intelligence, analytics, and data-driven decision-making
Please revert to hr@ie-cms.com