Data Warehouse Engineer

Khaoticen, founded in 2008, provides information technology strategies and solutions for the present and future business needs of our clients. Our reputation is based upon on-time delivery, high standards, and extensive follow-through support.

Our leadership team comprises highly experienced business leaders, entrepreneurs, and security experts with decades of experience in creating cutting-edge IT solutions, combining strong commercial acumen with expert knowledge and skill. Our technical staff possesses immeasurable hands-on experience while continuously upgrading and mastering new trends. This deep knowledge of existing and emerging technologies enables us to implement tech solutions the right way for our clients in tech, finance and insurance companies, telco providers, as well as companies working in energy, heavy industry, and the public sector.

When it comes to hiring, we commit to culture first. We turn up each day because we care about what we do, and believe an enjoyable, creative workplace with like-minded people is the secret to high-quality output. Experience the support of an enthusiastic team, a friendly social environment, managers who listen, professional development resources, and a people-first workplace culture.

Main Duties and Responsibilities:

• Design, develop, and maintain ETL processes to extract, transform, and load data from diverse sources
• Build and maintain scalable data warehouse solutions to support reporting and analytics
• Handle large datasets while ensuring data quality, consistency, and optimal performance
• Collaborate with BI developers, data analysts, and stakeholders to gather and interpret data requirements
• Monitor, troubleshoot, and optimize data pipelines and workflows
• Design and implement dimensional data models (e.g. star and snowflake schemas)
• Document data architecture, transformation logic, and technical specifications
• Ensure adherence to data governance, security, and privacy standards
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Specialized Knowledge:

• Deep understanding of data warehousing concepts and architecture
• Expertise in dimensional modeling, surrogate keys, and Slowly Changing Dimensions (SCD)
• Proficiency in ETL/ELT tools: Oracle Data Integrator (ODI), Informatica, Talend, Apache NiFi, SSIS, dbt
• Strong SQL skills including CTEs, window functions, indexing, and performance tuning
• Experience with platforms such as Snowflake, Redshift, BigQuery, Azure Synapse, Teradata, and Oracle
• Familiarity with data modeling tools: Erwin, PowerDesigner, dbt
• Scripting and automation experience using Python, Bash, or PowerShell
• Understanding of data privacy regulations (GDPR, HIPAA), access controls, and encryption
• Experience integrating DWH with BI tools like Power BI, Tableau, Looker, and Qlik
• Knowledge of DevOps practices in data engineering: CI/CD, Git, automated testing/deployment
• Knowledge of the following Oracle Technologies: Oracle Analytics Cloud, Oracle Integration Cloud, Autonomous Data Warehouse, OCI Data Science

Professional Experience:

• 2-4 years of hands-on experience in data engineering or data warehousing roles
• Solid experience in developing and maintaining ETL/ELT processes in production environments
• Practical experience working with relational databases and large datasets
• Involvement in designing dimensional data models and implementing data pipelines
• Experience collaborating with BI developers, analysts, and business users on data requirements
• Exposure to at least one cloud data platform (e.g. ADW, Snowflake, Redshift, BigQuery, or Azure Synapse)
• Familiarity with version control tools (e.g., Git) and basic CI/CD practices is a plus
• Prior experience with modern ETL tools and scripting (Python, Bash) preferred