Data Architect

The Data Architect will design and govern the enterprise data. architecture that enables scalable analytics, reporting, and data-driven decision-making across the organization. This role is responsible for integrating data from multiple enterprise systems, including APIs, operational and relational databases, and transforming and consolidating data into Teradata for analytics consumption. The position acts as a bridge between onsite teams, business stakeholders, and engineering teams to deliver trusted, scalable, and actionable insights that support organizational goals.

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) and Data Warehousing, Metadata Management and 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.
• Reduce 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.