Data Architect – Enterprise Data & AI Solutions

Experience Required: 8+ Years
Salary: Best in Industry

We are looking for a visionary Data Architect who can translate enterprise data into scalable, reliable, and AI-driven architectures. If you have a strong foundation in data modeling, cloud data platforms, and data modernization, and are excited about integrating Generative AI (GenAI) to unlock predictive insights, this role is for you.
This is an opportunity for someone who thrives at the intersection of enterprise strategy, advanced analytics, and next-generation AI adoption.

• Design scalable data models, warehouses, lakes, and lakehouse solutions.
• Build data pipelines to support advanced analytics, reporting, and predictive insights.
• Integrate GenAI frameworks to enhance data generation, automation, and summarization.
• Define and enforce enterprise-wide data governance, standards, and security practices.
• Drive data modernization initiatives, including cloud migrations.
• Collaborate with stakeholders, engineers, and AI/ML teams to align solutions with business goals.
• Enable real-time and batch insights through dashboards, AI-driven recommendations, and predictive reporting.
• Mentor teams on best practices in data and AI adoption.

• Strong background in RDBMS design, data modeling, and schema optimization.
• Advanced SQL skills, including performance tuning and analytics functions.
• Proven expertise in data warehouses, data lakes, and lakehouse architectures.
• Proficiency in ETL/ELT tools (Informatica, Talend, dbt, Glue).
• Hands-on with cloud platforms (AWS Redshift, Azure Synapse, GCP BigQuery, Snowflake).
• Familiarity with GenAI frameworks (OpenAI, Vertex AI, Bedrock, Azure OpenAI).
• Experience with real-time streaming (Kafka, Kinesis, Flink) and big data ecosystems (Hadoop, Spark).
• Strong communication skills with the ability to present data insights to executives.

• 8+ years in data architecture, enterprise data strategy, or modernization programs.
• Hands-on with AI-driven analytics and GenAI adoption.
• Knowledge of enterprise frameworks (TOGAF, DAMA-DMBOK).
• Domain experience in financial, healthcare, or other enterprise verticals.
• A Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.

• Deep understanding of data governance, metadata, and enterprise data quality.
• Familiarity with AI/ML model pipelines and data science platforms.
• A collaborative mindset and proven ability to align technical designs with business needs.
• Strong problem-solving, adaptability, and leadership skills.

• Opportunity to design next-generation enterprise data & AI architectures.
• Exposure to cutting-edge GenAI platforms to accelerate innovation.
• Collaborate with experts across cloud, data engineering, and AI practices.
• Access to learning, certifications, and leadership mentoring.
• Competitive pay with opportunities for career growth and leadership visibility.

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