Database Architect/ Data Modeler in Dallas TX

Job Title: Database Architect/ Data Modeler

Location: Dallas TX (Onsite)

Job Summary:

We are seeking an experienced Database Architect / Data Modeler to design, implement, and maintain scalable and efficient database systems while creating robust data models that align with organizational needs. The ideal candidate will have a deep understanding of database technologies, data architecture, data modeling principles, data security and business requirements, particularly in SQL-based database systems and .NET application modernization initiatives, ensuring data is stored, structured, and accessed optimally.

Key Responsibilities:

1. Database Architecture:

1. Design and implement robust and scalable database systems to support application and business needs.
2. Establish standards for database design, access, and maintenance.
3. Define and implement data security protocols, backup strategies, and disaster recovery plans.
4. Evaluate and implement database technologies for structured and unstructured data (e.g., SQL, NoSQL, Azure Datastore).
5. Define and optimize database schemas, indexes, and partitioning strategies.
6. Optimize database performance, scalability, and reliability.

1. Data Architecture:

1. Define the overall structure for how data is collected, stored, and accessed as per enterprise-wide data strategies and governance policies.
2. Develop data integration workflows and pipelines.
3. Ensure compliance with data privacy (PII) and security regulations (e.g., GDPR, CCPA).
4. Establish data quality standards and validation processes.

1. Data Modeling:

1. Create conceptual, logical, and physical data models to meet business and technical requirements.
2. Conduct detailed Fit-Gap analysis on data models to identify discrepancies between current and target states
3. Optimize existing data models to enhance performance and scalability within SQL databases.
4. Design and maintain entity-relationship (ER) diagrams, metadata repositories, data dictionaries and definitions.
5. Define data relationships, primary/foreign keys, and constraints to ensure integrity.
6. Collaborate with stakeholders to align data models with reporting and analytical needs.

1. Azure Data Ecosystem:

1. Design the architecture focused on modernizing legacy .NET systems and leveraging Azure services (e.g., Azure SQL, Azure Cosmos DB, ADLS, and Azure functions etc.).
2. Design and deploy solutions in cloud-based environments using best practices.
3. Monitor and troubleshoot Azure data workflows to ensure reliability and efficiency.

Qualifications:

1. Technical Skills:

1. Must Have

1. Minimum 10 years of experience with 5 years of experience in database design, data architecture, and data modeling.
2. Hands-on experience with relational and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB).
3. Proficiency with data modeling tools (e.g., ERwin, ER/Studio, PowerDesigner, Visio).
4. Strong knowledge of SQL, database design principles, and optimization techniques including performance tuning.
5. Expertise in data integration tools (e.g., Talend, Apache Kafka, Informatica).
6. Hands-on experience with Azure SQL, Data Factory, Synapse, and related services.
7. Prior experience in Agile/Scrum development methodologies is mandatory - sprint planning, stand-ups, and retrospectives.
8. Familiar with Azure DepOps and other Azure services.
9. Proficiency in creating and presenting documentation, diagrams, and reports.

1. Nice to have:

1. Familiarity with big data and data warehouse technologies (e.g., Hadoop, Spark, Redshift, BigQuery) and ETL processes.
2. Familiarity with cloud data platforms (e.g., Snowflake, AWS Redshift, Azure SQL).
3. Knowledge of data governance frameworks and regulatory compliance.
4. Proficiency in scripting languages (e.g., Python, Shell) for automation and ETL processes

1. Soft Skills:

1. Strong communication, interpersonal and stakeholder management skills.
2. Ability to work with cross-functional teams and drive consensus.
3. Strong analytical and problem-solving skills
4. Work effectively in an onshore-offshore model, facilitating seamless collaboration and communication.
5. Ability to provide technical guidance and mentor junior team members.