Anshuman Silori — CEO

I’m a Data Architect and Data Strategist with 9+ years of experience designing enterprise-grade data ecosystems, building real-time analytics platforms, and enabling companies to scale with a modern data stack. My work sits at the intersection of Data Engineering, Cloud Architecture, AI/ML, and System Design. I specialize in multi-cloud deployments (AWS, GCP, Azure) and building open, interoperable data platforms using Apache Hudi, Iceberg, and Delta Lake — powering everything from live commerce decisions to ESG intelligence platforms. Over the years, I’ve led architectural programs that unify streaming + batch, integrate RAG-based AI agents, and deliver secure, governed data at scale using DataHub, IAM, RLS, and GDPR-compliant standards. If there’s one pattern across my work, it’s this: turning real-time data into business leverage. 📌 What I Do Well Design & scale Lakehouse architectures on Databricks, Delta, S3 Build sub-second ingestion pipelines with Kafka, Kinesis, and Flink Architect AI-powered knowledge systems using RAG + MCP Migrate legacy stacks (Teradata/Oracle) to Snowflake & Redshift Implement Data Governance, Lineage, and internal Data Portals Deliver "secure-by-design" systems using IAM, encryption, and RLS 💡 Recent Impact At Blinkit, I led the architecture for a Real-Time Commerce Engine built on a multi-cloud platform, merging streaming + warehousing with open table formats. At GIST Impact, I built an ESG Intelligence Platform and GenAI chatbot enabling users to query satellite data and sustainability documents with natural language. 🛠️ Tech Arsenal AWS (EKS, Lambda, EMR), Databricks, Snowflake, Apache Kafka, Flink, Iceberg, Hudi, Trino, Terraform, Kubernetes, Python, DBT, Airflow, DataHub, MCP, React, FastAPI — and everything required to run modern data platforms end-to-end. 🎯 What Drives Me I believe modern data teams need more than pipelines — they need platform thinking, openness, and AI-first design. My goal is to help companies build systems that are real-time, governed, scalable, and ready for AI.

Stackforce AI infers this person is a Data Architect specializing in scalable data ecosystems and real-time analytics.

Experience: 12 yrs 11 mos

Skills

Data Engineering
Business Intelligence
Machine Learning

Career Highlights

Expert in building real-time analytics platforms.
Led multi-cloud data architecture initiatives.
Specialized in data governance and compliance.

Work Experience

Blinkit

Senior Lead Engineer (9 mos)

GIST Impact

Lead Data Engineer (1 yr 3 mos)

Country Delight

Senior Data Engineer (1 yr 10 mos)

Cashify

Data Engineer (1 yr 1 mo)

DecisionTree Analytics & Services

Data Engineer (4 yrs 1 mo)

Research Scholars

Research Executive (4 yrs 1 mo)

Education

Data Analyst at Great Learning

bachelor of technology at DIT UNIVERSITY

Anshuman Silori

CEO

India12 yrs 11 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in building real-time analytics platforms.
Led multi-cloud data architecture initiatives.
Specialized in data governance and compliance.

Stackforce AI infers this person is a Data Architect specializing in scalable data ecosystems and real-time analytics.

Contact

Skills

Core Skills

Data EngineeringBusiness IntelligenceMachine Learning

Other Skills

AWSGCPSnowflakeDatabricksPythonSQLScalaGoPySparkAirflowDBTKubernetesDockerStreamingData Warehousing

About

Experience

12 yrs 11 mos

Total Experience

2 yrs 5 mos

Average Tenure

9 mos

Current Experience

Blinkit

Senior Lead Engineer

Aug 2025 – Present · 9 mos · Gurugram, Haryana, India · On-site

Senior Lead Business Intelligence Engineer | Lead Data Engineer | Driving Data-Driven Transformation
I am a results-driven Senior Lead Business Intelligence Engineer with proven expertise in building and scaling data platforms, BI ecosystems, and advanced analytics solutions that empower business leaders with actionable insights. With experience leading cross-functional teams and architecting modern data infrastructure, I specialize in transforming raw data into strategic assets that accelerate growth, optimize decision-making, and drive measurable business impact.
At Blinkit, I lead initiatives that bring together Data Engineering, Business Intelligence, and Analytics to create high-performance data ecosystems capable of supporting real-time decision-making at scale. My work bridges engineering, business strategy, and analytics, ensuring that data is not only accessible but also impactful.
Core Expertise & Skills
Data Engineering & Architecture: Building scalable ETL/ELT pipelines, data lakes, and warehouses using AWS (Glue, Redshift, EMR, S3), GCP, Snowflake, Databricks, Spark, Kafka.
Business Intelligence & Analytics: Designing enterprise BI solutions with Power BI, Tableau, Looker, QuickSight, enabling self-service and data democratization.
Programming & Automation: Proficient in Python, SQL, Scala, Go, PySpark, with strong focus on performance optimization and automation.
Data Strategy & Leadership: Partnering with business leaders, product managers, and engineering teams to define data roadmaps, governance, and analytics strategy.
Cloud & Big Data Ecosystems: Expertise in AWS, GCP, Azure, big data frameworks, streaming platforms, and orchestration tools (Airflow, DBT, Kubernetes, Docker).
Machine Learning & GenAI Foundations: Experience supporting data pipelines for MLOps, Generative AI, RAG systems, vector databases, and model deployment.

Data EngineeringBusiness IntelligenceAWSGCPSnowflakeDatabricks+9

Gist impact

Lead Data Engineer

May 2024 – Aug 2025 · 1 yr 3 mos · Noida, Uttar Pradesh, India · On-site

Engineer | GIST Impact (June 2024 – Present)
Led a team of 8+ data engineers and analysts in the design, development, and delivery of scalable data solutions on AWS, with a focus on integrating GenAI and optimizing MLOps workflows for financial and sustainability analytics.
GenAI-Powered ESG Analytics Platform: Spearheaded the development of a GenAI-enhanced platform on AWS that leverages LLMs to automate the extraction, analysis, and reporting of ESG data from unstructured sources (e.g., sustainability reports, news articles). This initiative reduced manual effort by 60%, accelerated report generation by 40%, and improved the accuracy of ESG risk assessments. Key technologies included:
MLOps for Scalable ESG Risk Models on AWS: Designed and implemented a robust MLOps pipeline on AWS for deploying and monitoring machine learning models used in ESG risk assessment, credit risk modeling, and investment forecasting. This involved:
Automating model training and deployment using Kubeflow on AWS EKS.
Implementing model versioning and rollback mechanisms using MLflow.
Setting up real-time monitoring dashboards using Amazon CloudWatch to track model performance and data drift.
Establishing a continuous training pipeline to ensure models remain up-to-date with evolving ESG factors.
Scalable Data Pipelines for ESG Data on AWS: Designed and implemented data pipelines processing over 50 million records monthly, optimizing ETL runtime by 40% using AWS Glue and PySpark. This involved:
Developing reusable PySpark libraries for data transformation and validation.
Optimizing Glue jobs for performance and scalability using dynamic partitioning and efficient data formats (Parquet, ORC).

AWSMLOpsGenAIData EngineeringData AnalyticsPySpark+4

Country delight

Senior Data Engineer

Jul 2022 – May 2024 · 1 yr 10 mos · Gurugram, Haryana, India

Managed a team of 6+ engineers, delivering high-performance AWS-based data solutions, with a focus on advanced data warehousing and ETL processes.
Scalable Data Warehouse Implementation on AWS: Led the design and implementation of a scalable data warehouse on AWS using Redshift, optimizing data storage and query performance for business intelligence. This initiative improved data accessibility and reduced query response times by 50%. Key achievements:
Designed the data warehouse schema, incorporating star and snowflake schemas for efficient data retrieval.
Implemented ETL pipelines using AWS Glue and PySpark to extract data from various sources, transform it, and load it into Redshift.
Optimized Redshift performance by implementing distribution keys, sort keys, and table partitioning strategies.
Real-time Data Ingestion and Processing Pipeline on AWS: Designed and implemented a real-time data ingestion and processing pipeline using Amazon Kinesis and Spark Streaming to capture and process high-velocity data streams. This enabled real-time analytics and decision-making. Key components:
Configured Kinesis Data Streams to ingest real-time data from various sources, including application logs, sensor data, and customer interactions.
Developed Spark Streaming applications to process and transform the streaming data, performing aggregations, filtering, and enrichment.
Loaded the processed data into Redshift for real-time analysis and visualization.
Built ETL pipelines processing 20M+ records daily, leveraging AWS Glue, Lambda & Step Functions.
Developed and maintained data warehousing solutions on AWS Redshift, optimizing data retrieval and reporting.
Automated data workflows using Airflow, ensuring seamless data processing & reporting.

AWSRedshiftETLPySparkKinesisAirflow+1

Cashify

Data Engineer

Jun 2021 – Jul 2022 · 1 yr 1 mo · Gurugram, Haryana, India

Designed and implemented data solutions focused on improving data quality, processing efficiency, and building robust ETL pipelines.
Data Quality Framework on AWS: Designed and implemented a data quality framework on AWS to ensure the accuracy, completeness, and consistency of data across various systems. This framework included:
Developing data validation rules and checks using AWS Glue and Great Expectations.
Implementing data profiling and monitoring processes to identify and resolve data quality issues.
Establishing data governance policies and procedures to maintain data integrity.

AWSETLData QualityGreat ExpectationsData Engineering

Decisiontree analytics & services

Data Engineer

May 2017 – Jun 2021 · 4 yrs 1 mo · Gurugram, Haryana, India

Contributed to end-to-end data engineering initiatives at Decision Tree Analytics, specializing in ETL
processes using Talend for seamless data integration across Redshift, MySQL, and other sources. Implemented efficient data transformations to ensure data accuracy and consistency. Leveraged Tableau
for visualizing insights derived from integrated datasets, enabling stakeholders to make data-driven
decisions. Collaborated with teams to integrate and analyze Google Analytics data, enhancing
understanding of user behavior and optimizing business strategies. Played a key role in developing
scalable data architectures that supported advanced analytics and reporting capabilities within the
organization.  Designed and implemented ETL processes using Talend to efficiently integrate and transform data
from diverse sources including Redshift, MySQL, and other databases.  Developed and maintained data pipelines for seamless data flow and transformation, ensuring
accuracy and consistency in data processing.  Utilized Tableau for visualizing and presenting actionable insights derived from integrated
datasets, empowering stakeholders to make informed decisions.
 Collaborated with teams to incorporate Google Analytics data into analytical workflows, enhancing
understanding of user behavior and optimizing business strategies.  Contributed to the development of scalable data architectures to support advanced analytics and
reporting capabilities, driving data-driven initiatives within the organization.  Orchestrated ETL processes using Talend to seamlessly integrate and transform data from various
sources, including AWS S3 buckets, Redshift, MySQL, and other databases.  Designed and maintained scalable data pipelines utilizing AWS Lambda for automated data
processing and workflows.  Leveraged AWS Redshift for data warehousing and optimized querying performance to support
advanced analytics on big data sets.