Senior Data Engineer

Houlihan Lokey•Los Angeles, CA

10d•$190,000 - $200,000

About The Position

Maintain data warehouse infrastructure, ensuring the integrity, performance, and reliability of our data warehouse systems, supporting business intelligence and analytics efforts across the organization. Implement, and manage robust ETL processes to support data integration from multiple sources. Develop and maintain scalable data warehouse solutions to accommodate growing data needs. Optimize and tune data warehouse performance for efficient data retrieval and storage. Collaborate with data analysts, business stakeholders, and IT teams to understand data requirements and deliver effective solutions. Ensure data quality and integrity through data cleansing, and validation techniques. Monitor and troubleshoot data pipelines and warehouse systems to ensure continuous and reliable operation. Develop and enforce data warehouse architecture standards and best practices. Document data flows, architecture, and processes.

Requirements

Bachelor’s degree or foreign equivalent in Computer Engineering, Information Science and Engineering, Computer Science or a closely related field plus 6 years of post-baccalaureate experience in the job offered or any or any Data Engineering job titles.
6 years of experience must include: (1) building and implementing ETL pipelines to populate data marts and enterprise data warehouses, (2) relational database management systems (RDBMS) (3) data warehousing and data analysis and validation with SQL (4) data modeling techniques and tools (5) creating custom data visualizations with Tableau or IBM Cognos for advanced analytical experiences (6) data governance and data quality best practices (7) liaising with cross-functional teams to ensure alignment of data-driven recommendations with overall business goals.

Responsibilities

Maintain data warehouse infrastructure, ensuring the integrity, performance, and reliability of our data warehouse systems, supporting business intelligence and analytics efforts across the organization.
Implement, and manage robust ETL processes to support data integration from multiple sources.
Develop and maintain scalable data warehouse solutions to accommodate growing data needs.
Optimize and tune data warehouse performance for efficient data retrieval and storage.
Collaborate with data analysts, business stakeholders, and IT teams to understand data requirements and deliver effective solutions.
Ensure data quality and integrity through data cleansing, and validation techniques.
Monitor and troubleshoot data pipelines and warehouse systems to ensure continuous and reliable operation.
Develop and enforce data warehouse architecture standards and best practices.
Document data flows, architecture, and processes.