Data Architect

The core responsibilities for the job include the following:

Data Architecture and Strategy:

• Design enterprise data architecture, data models, and integration frameworks.
• Define data standards, governance practices, and architectural best practices.
• Establish scalable solutions for data ingestion, transformation, and consumption.
• Develop and maintain the analytics data roadmap aligned with business objectives.

Data Integration and Engineering:

• Build and oversee ETL/ELT pipelines to extract, transform, and load data into Teradata. Integrate data from Jira, GitHub/GitLab/Azure DevOps, SQL Server, APIs, and other enterprise systems.
• Ensure data quality, consistency, lineage, and performance optimization across the platform.
• Design reusable and scalable data transformation frameworks.

Analytics Enablement:

• Create analytics-ready datasets to support operational, engineering, and business reporting.
• Enable Power BI dashboards, KPI reporting, executive scorecards, and self-service analytics.
• Partner with analytics teams to identify opportunities for data-driven improvements.
• Drive data storytelling practices to transform data into meaningful business insights.

Stakeholder Engagement and Leadership:

• Partner with onsite stakeholders and cross-functional teams to define and deliver analytics solutions.
• Translate business requirements into scalable technical architectures.
• Provide technical leadership, mentoring, and architectural guidance to data and analytics teams.
• Lead architecture reviews and promote best practices across projects and programs.
• Present analytics strategies, recommendations, and insights to leadership teams.

Requirements:

• Required Skills: Teradata, SQL Server, Advanced SQL, Python ETL/ELT Design, Data Integration, and Data Transformation Frameworks; API Integration, Operational Data Integration, and Enterprise Data Management; Data Modeling (Star Schema, Snowflake Schema, Dimensional Modeling); Data Warehousing Metadata Management; Data Lineage; Power BI and Analytics Reporting; Data Governance; Data Quality; and Performance Optimization.
• Strong Data Storytelling and Business Communication Skills, Stakeholder Management, and Cross-Functional Collaboration.
• Expected Outcomes: Centralized and scalable enterprise analytics platform.
• Reliable automated data pipelines and reporting solutions. Improved data quality, consistency, and governance across integrated data sources.
• Enable leadership teams with actionable insights and performance metrics.
• Reduced manual reporting efforts through automation and standardization.
• Improved business visibility through analytics, dashboards, and data storytelling. Increased adoption of self-service analytics and data-driven decision-making.
• Strong stakeholder satisfaction through delivery of trusted analytics capabilities.

Preferred Experience:

• 12+ years of experience in data architecture, data engineering, data warehousing, and analytics platforms.
• Experience working with global/onsite stakeholders and cross-functional teams.
• Experience leading enterprise-scale analytics and reporting initiatives.
• Knowledge of cloud data platforms and modern data engineering practices is a plus.