When you join Hines, you will embark on a career journey fueled by vision and guided by leaders who set the standards of our industry. Our legacy is rooted in innovation and excellence, earning us a spot-on Fast Company’s esteemed annual list of the World’s Most Innovative Companies for 2024. Discover endless opportunities to grow and make your mark at Hines.

As an ETL Developer/Data Engineer with Hines, you will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing existing data systems and building them from the ground up. Responsibilities include, but are not limited to: 

• Maintain and provide enhancements to data architecture within new/existing systems including Data Warehouse
• Recommend and implement process to improve data quality, data reliability, and database performance
• Employ variety of ETL and integration tools for system and data integrations
• Architect solutions that support data scientist and business stakeholders
• Conduct ETL testing and data transformation testing
• Develop data models for data science team that can be utilized for data mining
• Maintain source to target documentation and process flow documentation
• Take on DBMS responsibilities and wear multiple hats such as: ETL’s, serve as SQL Server DBA – Processes/Job/Error Handling/Troubleshooting/Scheduling, etc.

Minimum Requirements include:

• Bachelor's degree in Computer Science or Information Technology from an accredited institution
• ETL Tools: SSIS 5+ years, Azure Data Factory (ADF) 2+ years
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. (4+ years of SQL), and working knowledge of Azure
• Proficient in MS SQL Server database including setting indexes, database security, and backups
• Commercial real estate experience preferred
• Data Testing: 3+ years
• Fundamental knowledge of data warehouse concepts
• Data Warehouse testing: 2+ years
• Javascript 1+ years, C# 1+ years
• Experience in data duality, source systems analysis, and business rules validation
• Ability to write and understand Source to Target documentation
• Detail oriented and meticulous approach to duties
• Keep our data separated and secure.  Familiarity with data and cybersecurity.
• Good analytical skills
• A knack for independent and group work
• Capacity to successfully manage a pipeline of duties with minimal supervision
• Must be located in Houston, TX and willing to work a hybrid schedule

At Hines, we strive for excellence as a leading global real estate investment manager, driven by our by our belief that real estate is fundamentally about people. Our diverse portfolio spans $93.2 billion¹ of assets across such property types as living, office, retail, mixed-use, logistics and life science projects – all designed to enhance value, connection and inspiration. Our strategic approach integrates local expertise with global knowledge, taking calculated risks aligned with our convictions to exceed expectations and tailor solutions to our clients' needs.

While our projects are renowned for enhancing cities and pioneering sustainable practices, we recognize that the true driving force behind Hines' success is our 5,000 dedicated employees in 30 countries who draw on our 65-year history to build the world forward. This is why we prioritize investing in our people, offering comprehensive training, competitive compensation, robust benefits and generous vacation packages. By centering our focus on the growth and wellbeing of our team, we cultivate an inclusive environment where everyone, including our clients, can thrive.

Hines is proud to be named to Fast Company’s prestigious annual list of the World’s Most Innovative Companies for 2024. ¹Includes both the global Hines organization and RIA AUM as of December 31, 2023.

We are an equal opportunity employer and support workforce diversity

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