DR Decisions Resources LLC is hiring a Lead Product AI Data Engineer & Architect in Bangalore (hybrid). In this role, you will design, build, and optimize end-to-end data architecture and scalable data platforms that support product analytics and AI/ML initiatives, with technical leadership across modeling, pipelines, quality operations, and team mentorship.
Role Focus
You will lead product-level data architecture to ensure scalability and reliability while aligning with analytics and AI/ML use cases. The work includes building production-ready pipelines, establishing dimensional data models, and ensuring datasets are validated, documented, and ready for analytics, experimentation, and machine learning.
Responsibilities
- Own and evolve product-level data architecture for 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 data models, including star and snowflake schemas.
- Design and maintain fact and dimension tables with correct grain, performance, and consistency.
- Help enforce architecture and modeling standards, naming conventions, and ETL/ELT best practices across product teams.
- Provide architectural guidance to align data solutions with product requirements, platform constraints, and AI/ML needs.
- Partner with Product Managers, Data Scientists, Analysts, and Engineers to translate requirements into well-architected models and pipelines.
- Prepare, validate, and document datasets for analytics, experimentation, and machine learning.
- Support and evolve product event tracking architectures 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.
- Diagnose and resolve complex data issues impacting analytics, AI workflows, or product features.
- Mentor data engineers through architecture reviews, code reviews, and design discussions.
- Participate in cross-team data architecture, modeling, and pipeline design reviews.
- Collaborate with platform, cloud, and security teams to deliver scalable, secure, production-ready data architectures.
- Drive enterprise-grade product and AI data platform outcomes, including analytics- and AI-ready datasets built on strong dimensional foundations.
Required Qualifications
- 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 (star schemas, snowflake schemas, fact tables, 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.
Technology Stack
SQL, Python, Snowflake, Data Bricks, BigQuery, Amazon Redshift, dbt, Airflow, Fivetran, Segment, Power BI, Tableau, SAP BusinessObjects, AWS, Azure, GCP, JSON
Additional Preferred Experience
- Experience with cloud data warehouses such as Snowflake, Data Bricks, BigQuery, or Amazon Redshift.
- Familiarity with tools including dbt, Airflow, Fivetran, and Segment.
- Experience with event-driven or semi-structured data (JSON, logs, clickstream).
- Exposure to BI and visualization tools such as 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 focused on creating and maintaining internal tools that convert unstructured data available on the internet into structured data. This structured data is then cross referenced and analyzed, and it will be exposed to multiple products provided to customers. The team also collaborates with others to create a service mesh structure that communicates through asynchronous queue services hosted in AWS.
Work Location and Schedule
This is a hybrid role based in Bangalore, India, working 2-3 days per week.
