Shiv Shankar

About Shiv Shankar

I am a Senior Data Engineer at JobSavior, specializing in architecting high-scale, cloud-native data platforms that power real-time insights, hiring intelligence, and data-driven decision-making across large career and placement ecosystems.I lead the design and ownership of end-to-end data infrastructure across AWS, GCP, and Azure, building resilient, low-latency systems that handle complex data flows at scale. My core strength lies in real-time streaming architectures using Apache Kafka, enabling event-driven platforms, near real-time analytics, and intelligent automation.With a strong foundation in distributed systems, data modeling, and cloud data engineering 🧠, I build and optimize data lakes, warehouses, and pipelines that are secure, scalable, and performance-driven. I work closely with product, analytics, and leadership teams to translate business vision into production-grade data solutions that directly impact growth, efficiency, and user experience.I am deeply focused on engineering excellence, reliability, and scalability — setting standards, driving best practices, and mentoring engineers to build systems that last. I thrive in environments where data is mission-critical and scale is non-negotiable.Core Expertise:Real-Time Data Platforms & Streaming Architectures Apache Kafka, Event-Driven Systems, Low-Latency Pipelines Cloud-Native Data Engineering (AWS, GCP, Azure) Data Lakes, Warehouses, ETL/ELT, Distributed Processing Data Architecture, Data Modeling, Performance Optimization Hiring Intelligence, Analytics Platforms, Decision Systems

Experience

1. Senior Data Engineer

   Jobsavior

   Jun 2024 — Present · Gurugram, IN

   As a Senior Data Engineer at JobSavior, I lead the design and development of scalable, cloud-native data platforms that enable real-time insights, hiring intelligence, and data-driven decision-making across large-scale placement and career ecosystems.Responsibilities & ImpactArchitect and own end-to-end data pipelines across AWS, GCP, and Azure, ensuring scalability, security, and high availability.Design and implement batch and real-time streaming systems using Apache Kafka, enabling event-driven architectures and near real-time analytics.Build and optimize cloud data lakes and data warehouses using AWS S3, Redshift, Glue, GCP BigQuery, Cloud Storage, Dataflow, and Azure Data Lake, Synapse, Data Factory.Develop high-performance ETL/ELT workflows using SQL and distributed processing frameworks to deliver analytics-ready datasets.Lead Kafka ecosystem management including topic design, producers/consumers, schema evolution, fault tolerance, and throughput optimization.Implement data modeling, partitioning, and query optimization strategies to support BI dashboards, reporting, and advanced analytics.Establish data quality, monitoring, observability, and alerting frameworks to ensure platform reliability and trust in data.Drive cloud cost optimization, performance tuning, and capacity planning across compute and storage layers.Enforce data governance, IAM, encryption, and compliance best practices in multi-cloud environments.Collaborate with product, analytics, and leadership teams to translate business requirements into scalable technical solutions.Mentor junior engineers and contribute to architecture decisions, standards, and best practices.

Education

• Amity University

  Bachelor of Technology - BTech, Computer Software Engineering