Data Architect
Location: Cary, NC
Contract
Mandatory Skills: Data Modeling, ETL Design, SQL
Job Description
Key Responsibilities
Database Design and Modeling: Develop conceptual, logical, and physical models for databases based on organizational needs. This involves creating entity-relationship diagrams, defining data flows, and ensuring that the database structure supports business objectives.
Requirements Analysis: Work closely with stakeholders including business analysts, developers, and project managers to gather, analyze, and validate requirements for data storage, retrieval, and reporting.
Database Implementation: Translate data models into actual database structures using relational (SQL) or non-relational (NoSQL) database management systems. Implement tables, indexes, relationships, and constraints as needed.
Optimization and Performance Tuning: Monitor and analyze the performance of databases. Optimize query performance, ensure proper indexing, and recommend improvements to maximize efficiency.
Data Integrity and Security: Establish and enforce standards for data integrity, consistency, and security. Implement measures such as access controls, encryption, and backup strategies to protect sensitive information.
Documentation: Prepare and maintain detailed documentation of database designs, schemas, data dictionaries, workflows, and procedures for future reference and auditing purposes.
Maintenance and Upgrades: Plan for and execute upgrades to database systems, including patches, migrations, and scaling strategies. Ensure minimal downtime and data loss during maintenance activities.
Collaboration: Work with software engineers, data analysts, and IT teams to integrate databases with existing applications, reporting tools, and business intelligence platforms.
Troubleshooting: Diagnose and resolve database-related issues, including connectivity problems, data corruption, and system errors.
Data Extraction: Gather data from various structured and unstructured sources, including flat files on cloud storage platforms, ensuring data completeness and accuracy.
Data Transformation: Cleanse, standardize, and convert raw data into usable formats. Apply business logic, validation rules, and enrichment processes to prepare data for analysis and reporting.
Data Loading: Efficiently load transformed data into target databases, data warehouses, or data lakes, maintaining referential integrity and minimizing system disruptions.
Workflow Automation: Develop and schedule automated ETL jobs using tools such as SSIS, Informatica, Talend, or scripting languages. Monitor job execution, troubleshoot issues, and optimize job performance for reliability and scalability.
Required Skills and Competencies
Technical Proficiency: Extensive knowledge of database management systems (DBMS) such as MySQL, PostgreSQL, Oracle, SQL Server, MongoDB, and others.
Data Modeling: Expertise in developing normalized and denormalized data models, understanding relationships, data types, and normalization principles.
Programming Skills: Familiarity with SQL and procedural languages (PL/SQL, T-SQL), as well as scripting languages such as Python or Shell for automation.
Experience with designing, implementing, and managing databases in a business environment.
Proven track record of successful database projects, including migration, integration, and performance tuning.
Hands-on experience with data modeling tools (such as Erwin, Lucid chart, or Microsoft Visio).
Familiarity with modern development methodologies (Agile, DevOps) and version control systems (Git, SVN).