About the Role : We are looking for a highly hands-on Data Platform Engineer to join our AI Labs team in Bengaluru. This role will be responsible for architecting, building, and scaling our end-to-end data platform, bridging traditional data engineering with modern AI infrastructure.You will own the design and implementation of data pipelines, lakehouse architecture, multi-region data systems, and AI/ML-powered data processing workflows. From Change Data Capture (CDC) and ETL/ELT pipelines to LLM inference and multimodal data redaction, you will build reliable, scalable, and cost-efficient data infrastructure.Roles & Responsibilities : 1. End-to-End Data Architecture & Engineering : - Design, build, and maintain end-to-end data pipelines, covering CDC ingestion from production databases to production-grade lakehouse storage.- Develop and scale workflow orchestration using Temporal and data transformation pipelines using dbt.- Build standardized dimensional data models and optimized relational/materialized views to support analytics and business intelligence.- Modernize legacy data workflows by replacing traditional DAG runners and cron-based batch jobs with scalable orchestration frameworks.2. Multi-Region Architecture & Data Residency : - Design and implement multi-region data architectures across cloud environments, ensuring compliance with data residency and sovereignty requirements.- Establish secure data isolation mechanisms to ensure sensitive patient and transaction data remains within permitted geographical boundaries.- Build compliant cross-region replication, synchronization, failover, and data-routing mechanisms.3. AI/ML Integration & Multimodal Data Processing : - Integrate machine learning models into data pipelines to identify and redact sensitive PII/PHI across text, images, audio,



and video.- Build and operationalize embedding generation, LLM inference, and semantic search pipelines.- Develop scalable workflows for AI-powered data processing and multimodal content analysis.4. Lakehouse Infrastructure & Platform Enablement : - Design and optimize open lakehouse architectures using Apache Iceberg.- Implement efficient partitioning, ACID transactions, and time-travel capabilities for large-scale datasets.- Provision and manage secure, scalable Jupyter Notebook environments for data science and exploratory analytics.5. Cloud Infrastructure, DevOps & FinOps : - Design, deploy, and manage AWS infrastructure using Infrastructure as Code (Terraform or AWS CDK).- Establish cost-monitoring frameworks to track cost-per-outcome across data and AI pipelines.- Own production reliability through monitoring, alerting, data quality checks, and pipeline freshness tracking.Required Skills & Technical Expertise : - Robust experience in data engineering, data platform development, and large-scale distributed data systems.- Proficiency in SQL and Python for data engineering and pipeline development.- Hands-on experience building CDC-based ingestion and ETL/ELT pipelines.- Experience with workflow orchestration frameworks such as Temporal.- Working knowledge of dbt for data transformation and modeling.- Experience with Apache Iceberg or other modern lakehouse technologies.- Experience with AWS cloud infrastructure and Infrastructure as Code tools such as Terraform or AWS CDK.- Exposure to ML/LLM inference pipelines, embedding generation, and AI-powered data processing.Hiring Note : We are hiring for two complementary SE II positions from the same candidate pool. Both positions are individual contributor roles focused on deep technical architecture and execution, with no formal people-management or team-mentoring responsibilities. (ref:hirist.tech)

📌 Practo - Data Platform Engineer (Bengaluru)
🏢 Practo Technologies
📍 Bengaluru