Lead Product AI Data Engineer & Architect

DR Decisions Resources LLC is building and operating internal tools that turn unstructured data from across the internet into structured datasets that teams can cross reference and analyze. In this hybrid role based in Bangalore, India (2-3 days a week in office), you will lead the product-facing AI and data engineering architecture that supports product analytics and AI/ML initiatives, while partnering with Product, Data Science, Analytics, Engineering, and Platform teams.

What you’ll do

• Own and evolve product-level data architecture, ensuring scalability, reliability, and alignment with analytics and AI/ML use cases.
• Design and implement scalable, reliable data pipelines for product analytics, user behavior tracking, and AI/ML initiatives.
• Define and maintain enterprise-aligned dimensional models using star and snowflake schemas, including fact and dimension tables with correct grain, performance, and consistency.
• Help enforce architecture, modeling, and operational standards across product teams, including naming conventions and ETL/ELT best practices.
• Translate requirements into well-architected data models and pipelines by partnering with Product Managers, Data Scientists, Analysts, and Engineers.
• Prepare, validate, and document datasets used for analytics, experimentation, and machine learning.
• Support and evolve product event tracking architectures so event data remains aligned with dimensional models and downstream analytics.
• Implement monitoring, testing, and alerting for data quality, pipeline health, and freshness.
• Ensure integrity of fact and dimension data through validation, reconciliation, and automated checks, and resolve complex data issues that affect analytics, AI workflows, or product features.
• Provide technical mentorship through architecture reviews, code reviews, and design discussions, and participate in cross-team design reviews.
• Collaborate with platform, cloud, and security teams to deliver scalable, secure, production-ready data architectures.

Requirements

• Bachelor’s degree in engineering or master’s degree (BE, ME, B Tech, MTech, MCA, MS)
• Minimum 7+ years of professional experience in data engineering, analytics engineering, or data architecture-heavy roles
• Expert-level proficiency in SQL and relational database design
• Strong programming experience in Python for data pipelines and automation
• Deep hands-on experience with data architecture and dimensional modeling, including star schemas, snowflake schemas, fact tables, and dimension tables
• Strong understanding of slowly changing dimensions (SCDs), surrogate keys, grain definition, and hierarchical dimensions
• Experience designing and operating ETL/ELT pipelines for production analytics and AI/ML workloads
• Ability to influence technical outcomes through architectural leadership and collaboration

Technologies

SQL, Python, Snowflake, Data Bricks, BigQuery, Amazon Redshift, dbt, Airflow, Fivetran, Segment, Power BI, Tableau, SAP BusinessObjects, AWS, Azure, GCP, JSON

IT would be great if you also had

• Experience with cloud data warehouses such as Snowflake, Data Bricks, BigQuery, or Amazon Redshift
• Familiarity with tools such as dbt, Airflow, Fivetran, and Segment
• Experience working with event-driven or semi-structured data (e.g., JSON, logs, clickstream)
• Exposure to BI and visualization tools (Power BI, Tableau, SAP BusinessObjects)
• Familiarity with AWS, Azure, or GCP, including data governance and security best practices

About the team

You will join a team responsible for creating and maintaining internal tools that convert unstructured data from the internet into structured data for cross-referenced analysis. The resulting data is exposed to multiple customer products. The team also collaborates with others to build a service mesh structure that communicates through asynchronous queue services hosted in AWS.