Data Architect

• Design, implement, and maintain traditional and modern data infrastructures at staff level
• Combine relational databases, cloud technologies, and big data tools to create scalable, efficient, and secure data solutions
• Develop strategies for enterprise data integration, data quality, and optimized data access across cloud and on-premise systems
• Work on moderate to complex projects
• Deliver robust data models, pipelines, and warehouses using SQL, Python, PySpark, and traditional RDBMS platforms
• Apply product, project, or program management methodologies to data architecture projects
• Collaborate with stakeholders and teams to align data architecture projects with business goals and execute efficiently

• Proficiency with SQL and traditional RDBMS such as Oracle, SQL Server, or PostgreSQL
• Experience with AWS, Azure, or Google Cloud Platform for data architecture and storage
• Strong familiarity with Python and Py Spark
• Working experience with ETL/ELT processes and tools, including SSIS, Informatica, Azure Data Factory, or Databricks
• Proficiency with Python, PySpark, or R programming
• Excellent communication skills for stakeholder and team collaboration
• Proficiency in Product Management, Project Management, or Program Management philosophies and methodologies
• Preferred:
  Master’s degree in an analytics‑related field
• Preferred alternative: 4 years of professional experience in an analytics‑related field
• Preferred alternative:
  Bachelor’s degree in an analytics‑related field with 2 years of experience
• Experience with Databricks, Apache Spark, and Delta Lake
• Proficiency in Kafka, AWS Kinesis, or Azure Event Hubs
• Experience working with APIs to retrieve and integrate external data
• Experience developing APIs to provide data as a product
• Familiarity with CI/CD pipelines
• Knowledge of data governance frameworks and compliance standards such as GDPR and HIPAA
• Familiarity with Tableau, Power BI, or Looker
• Ability to remain sitting or standing for long periods while working on a computer, telephone, or other equipment
• Potential onsite interviews and meetings

Demonstrates expertise in designing and implementing data infrastructures, utilizing SQL, Python, and cloud technologies to create scalable data solutions. Proficient in data integration strategies and project management methodologies to align data architecture with business objectives.