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We are seeking for an Engineer to support AI and data initiatives by building and enhancing the data and analytics foundations that enable customer insights and GenAI-driven use cases. This role focuses on developing scalable data ingestion, transformation, taxonomy, and analytics capabilities that support dashboards, KPIs, trend analysis, and AI-assisted insight generation. The engineer works closely with analytics, engineering, and GenAI stakeholders to translate complex data into reliable, usable, and actionable insights.
Key Responsibilities:
Data & Analytics Enablement
Build and maintain datasets, metrics, and analytical views supporting dashboards, KPIs, trend analyses, and drill-down reporting
Develop and refine semantic layers and metric definitions to ensure clarity, consistency, and usability across analytics products
Support data visualization and reporting in tools such as Tableau or QuickSight
Data Engineering & Pipelines
Design and implement automated data ingestion and transformation pipelines for structured and unstructured data sources
Support taxonomy alignment, labeling, and metadata enrichment to improve discoverability and AI readiness
Build scalable data storage and transformation layers, including curated datasets and dbt-style models
Work closely with engineering teams to ensure ingestion correctness, pipeline stability, and data readiness
GenAI & Agentic AI Enablement
Support integration of analytics pipelines with GenAI and Agentic AI components used for insight generation and exploration
Apply GenAI tools to improve analytical workflows, automate repetitive tasks, and surface insights more efficiently
Help prepare datasets and metadata for RAG and AI-driven analytics use cases
Data Quality, Performance & Reliability
Apply data quality checks, validation logic, and monitoring to ensure accuracy and reliability of analytical outputs
Support optimization of data pipelines for performance, latency, and scalability
Contribute to documentation, data definitions, and usage guidance
Collaboration & Problem Solving
Collaborate with analysts, GenAI specialists, quality teams, and business stakeholders to deliver aligned solutions
Contribute to technical design discussions and solution reviews
Navigate ambiguous problem spaces with a structured and solution-oriented approach
Insight Generation & Business Alignment
Analyze complex datasets to identify relevant takeaways for the executive team
Validate whether analytical results align with business logic, operational realities, and customer behavior
Translate business requirements into clear technical specifications so analytical workflows and data outputs support underlying strategic needs
Who are you?
3+ years of experience in data engineering, analytics engineering, backend engineering, or data analytics roles.
Strong SQL skills and experience working with analytical datasets and metric development.
Hands-on experience with ETL/ELT pipelines, data ingestion frameworks, and API-based integrations.
Experience working with both structured and unstructured data.
Familiarity with data visualization tools such as Tableau, QuickSight, or similar.
Solid understanding of data modeling, data quality, and validation practices.
Nice to have
Experience supporting or integrating GenAI or Agentic AI solutions within analytics or data platforms.
Familiarity with cloud-based data architectures (AWS preferred).
Experience with customer behavior analytics, usage metrics, or quality indicators.
Exposure to metadata management, taxonomy design, or labeled datasets for AI use cases.
Core Skills & Attributes
Strong analytical thinking and attention to detail in metrics definition and data interpretation.
Ability to communicate technical concepts clearly to both technical and non-technical audiences.
Collaborative mindset with comfort working across teams and disciplines.
Interest in applying GenAI tools to enhance analytics and data-driven decision-making.
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