Data Architect

Brief Description

This position is responsible for designing and implementing strategic data initiatives across the Client, including enterprise data warehousing, metadata management, and machine learning solutions. The candidate must have extensive experience in data architecture, ETL development, advanced analytics, and Qlik Sense.

Design and implement strategic data initiatives such as:

• Enterprise Data Warehouse (EDW)
• Master Data Management
• Data Governance and Data Quality
• Metadata Management and Data Marts
• Administer and monitor automated and manual data integration and ETL jobs to verify execution and measure performance.
• Design and implement enterprise-wide metadata and information management programs.
• Develop enterprise conceptual, logical, and physical data models.
• Provide data architecture support to major application development initiatives in an agile environment.
• Implement program standards and procedures to support data warehouse administration.
• Provide technical advice on data management and design to application development teams, enterprise architects, and business stakeholders.

Develop ETL processes including:

• Source Dependent Extracts (RDBMS, APIs, flat files)
• Source Independent Loads
• Post-load processing
• Implement near real-time loads and Change Data Capture (CDC).
• Perform data mining and extraction from structured and unstructured data sources.
• Build, validate, deploy, and monitor machine learning models end-to‑end.
• Analyze large datasets to identify trends, patterns, and insights.
• Develop predictive systems and machine learning algorithms.
• Research and implement novel AI/ML approaches using modern platforms and frameworks.
• Deliver descriptive, predictive, and prescriptive analytics solutions.

• 8 years of progressively responsible experience in:
• Data warehousing and data integration
• Data modeling and ETL development
• Experience implementing corporate data architecture programs including:
• Enterprise data models
• Data policies, standards, and governance
• Metadata mapping and compliance monitoring
• Experience as an ML Engineer or Data Scientist with hands‑on ML model development and deployment.

• Oracle, Redshift, MySQL, Snowflake, SQL Server

• Informatica Power Center, Informatica IICS

• Qlik Sense, Tableau, Power BI

• Python, R, SQL (Hive, Pig desirable)
• Scala, Java, or C (preferred)

• Tensor Flow, PyTorch, OpenNN, H2O.ai, SparkML
• AWS Sage Maker, Azure Synapse Analytics, Google Big Query

• Descriptive, Predictive, Prescriptive Analytics
• Statistical & Mathematical Skills

• Statistical tests, distributions, regression, MLE

• k‑NN, Naive Bayes, SVM, Decision Forests

• Multi-variable Calculus