Alvarez & Marsal - Houston, TX
posted 2 months ago
Alvarez & Marsal is seeking a skilled Data Architect to join our corporate IT team. In this role, you will play a crucial part in expanding and designing our internal data warehouse and business intelligence functions, which support over 18 different business lines. Your primary responsibilities will include designing, building, and enhancing our SQL data warehouse, managing ETL processes, and working within Azure environments. You will also be tasked with troubleshooting data and database issues, ensuring that our data architecture is robust and efficient. As a Data Architect, you will be responsible for designing and commissioning new subject areas, as well as enhancing existing ones. This includes implementing new or upgraded cloud data strategies and Azure platforms. You will create Entity Relationship diagrams and write relational database queries, ensuring that database objects are created and maintained with referential integrity. Managing master data will also be a key responsibility, which includes creation, updates, and deletion of data as necessary. You will design, implement, and help maintain ETL migrations to Azure Data Factory, processing confidential data according to strict guidelines defined by subject area owners. Quality assurance of imported data will be essential, and you will work closely with business stakeholders and analysts to ensure data integrity. Participation in peer design reviews and development sessions will be expected, as well as developing data models and managing data acquisition, access analysis, and recovery processes. Collaboration with internal customers to capture requirements will be a significant part of your role, as will designing, creating, documenting, managing, and fulfilling user requests for new or existing datasets. Adhering to SDLC processes and standards will be critical to ensure proper coding practices are followed. You will also be responsible for training end users on new data elements and providing technical expertise on data storage structures, data mining, and data cleansing. Applying best practices in data pipeline and model design will be essential to achieve robust and flexible data solutions.