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Namratha
Putrev

Data Platform Lead  ·  Real-Time Streaming  ·  Retail Domain

Over 7 years of experience designing and delivering scalable data platforms and distributed systems — with a focus on real-time streaming, ETL optimisation, and production reliability for global retail clients. I bring both technical depth and team leadership to every engagement.

7+
Years Experience
7
Retail Clients
99.9%
Data Delivery SLA
Background & Approach

Engineering with Purpose.

With 7+ years of experience in data engineering and distributed systems, I specialise in building platforms that are reliable, high-throughput, and built to scale — particularly within the retail domain, where reducing time-to-market for pricing updates has a direct and measurable impact on client outcomes.

My core work spans near real-time streaming, ETL pipeline design, and cloud-based data architecture using Apache Kafka, Spark, Python, Scala, Databricks, Snowflake, Airflow, Elasticsearch, and SQL/NoSQL databases. I take ownership across the full delivery lifecycle — from architecture and implementation through to production stability and incident resolution — for global retail clients.

I've also been deliberate about integrating AI-assisted development into how I work. Using Cursor and Claude Code for spec-driven workflows, and Miro with GitHub MCP for design and review collaboration, I've helped reduce development cycle times by 30% and review turnaround by 40%.

Beyond the technical, I invest in team development — mentoring engineers, establishing engineering standards, and creating the conditions for high-quality, consistent delivery.

Outside of Work
🌿 Nature & Outdoors ✈️ Exploring Cultures 📚 Reading 🤝 Mentoring 🌍 Travel
Scalable Data Pipeline — Architecture Approach
📥
Data Sources
APIs · Databases · Event Streams · Files
↓ Ingestion Layer
⚡
Apache Kafka
Partitioned topics · Multi-namespace · 3x throughput
NRT
↓ Stream Processing
🔄
Spark Structured Streaming
Micro-batches · Checkpointing · Fault-tolerant
1,500+ rec/min
↓ Validation
✅
Integrity & Reconciliation
Offset checks · Row counts · Checksums
↓ Storage
🗄️
Databricks / Snowflake
Delta Lake · Elasticsearch · Object Storage
↓ Orchestration
🎛️
Airflow / AutoSys DAGs
Parallel execution · Monitoring · Alerting
50% faster deploys
Outcomes & Delivery

Measurable Impact

1,500+
Records/min in NRT pipeline — exceeding NFRs by 50%, enabling near-instant pricing updates
99.9%
Data delivery SLA maintained across all retail clients
40%
Reduction in recurring P1/P2 incidents through proactive Spark tuning
30%
Faster development cycles via AI-powered tools — Cursor & Claude Code
1,800+
Engineering hours saved annually across 5M-record Databricks batch jobs
10x
Larger datasets handled after JGraphT graph algorithm — unblocking high-volume client onboarding
Professional History

Work Experience

Periscope by McKinsey & Company
Nov 2024 – Present
📍 Bangalore
Senior Software Engineer
Global management consulting firm · Retail domain
  • Leading ETL, IETL & Near Real-Time data platform initiatives serving ~7 retail clients, owning architecture, delivery, and production stability.
  • Designed and implemented a high-throughput NRT ingestion pipeline using Apache Kafka + Spark Structured Streaming with fault-tolerant checkpointing, micro-batch offset tracking, and automated recovery — achieving 1,500+ records/min (exceeding NFRs by 50%), enabling near-instant product pricing updates that reduced time-to-market from hours to minutes and ensuring 99.9% data delivery SLA.
  • Designed a scalable relationship graph-building algorithm using JGraphT, resolving Spark executor memory issues — enabling the platform to handle 10x larger datasets without OOM failures and unblocking onboarding of high-volume retail clients.
  • Managed migration of competitor history from dual to single scorecard architecture — consolidating redundant storage, improving query performance by 30%, and enabling a unified competitive insights view that accelerated client decision-making.
  • Partnered with DevOps to build scalable Kafka infrastructure via multi-namespace topics — supporting a 3x increase in event throughput without additional infrastructure spend.
  • Migrated SBM & SC1 Auto Workflow pipelines from in-house Spark to Databricks with Airflow DAG integration — saving 25 min/job across 5M-record batches (~1,800+ hrs/year) with significant compute cost savings.
  • Owned P0–P3 production incident resolution, achieving a 95%+ on-time resolution rate and reducing recurring P1/P2 incidents by 40%.
  • Introduced DAG-level Spark configuration support, reducing deployment time by 50% and accelerating time-to-production for new client onboarding.
  • Leveraged Cursor and Claude Code for AI-first spec-driven development — automating code generation, test scaffolding, and documentation, achieving a 30% reduction in development cycle time.
  • Integrated Miro and GitHub MCP to automate design documentation and code review workflows, reducing review turnaround by 40% through real-time architect–developer collaboration.
  • Mentored engineers and led design & code reviews, contributing to measurable uplift in team velocity and code quality metrics.
ThoughtWorks
Jan 2022 – Nov 2024
📍 Bangalore
Senior Consultant, Developer
Global software consultancy
  • Led data architecture design sessions to build scalable pipelines using data lake and warehouse patterns.
  • Performed data analysis on large, multi-format datasets to enable business-critical decision making.
  • Improved Databricks job performance via PySpark optimizations, reducing overall processing cost.
  • Developed and maintained ETL pipelines ingesting, transforming, and loading data from heterogeneous sources.
  • Championed TDD and SOLID principles; mentored junior engineers through code reviews and technical huddles.
  • Collaborated with stakeholders, business analysts, and cross-functional client teams to deliver data solutions.
ONX Technologies
Oct 2020 – Jan 2022
📍 Bangalore
Software Development Engineer
Technology solutions provider
  • Built backend services and APIs using JavaScript, TypeScript, and relational and NoSQL databases.
  • Refactored and modernized legacy codebases to improve maintainability and performance.
  • Tracked and documented project changes using JIRA and Azure DevOps.
Katerra Technologies
Apr 2019 – Oct 2020
📍 Bangalore
Software Developer
Technology & construction firm
  • Delivered and maintained scalable system architecture supporting high-availability applications.
  • Collaborated across the SDLC from requirements gathering to production releases.
  • Built event-driven microservices-based applications.
Ruca Tech Data Science
Aug 2018 – Apr 2019
📍 Bangalore
Software Developer
Data science & technology firm
  • Generated automated reports using Python and Mailgun.
  • Worked with AWS services including SageMaker, Amazon Lex, and Amazon Polly.
  • Integrated email templates using HTML, CSS, and JavaScript.
  • Contributed to Python codebases for automated deployment across virtual machines.
Core Competencies

Technical Skills

Languages
PythonScalaJavaJavaScriptTypeScriptC / C++
Big Data & Streaming
Apache SparkPySparkApache KafkaSpark Structured StreamingDatabricksSnowflake
Databases
PostgreSQLMongoDBElasticsearch
DevOps & Orchestration
DockerKubernetesJenkinsApache AirflowAutoSys
AI & Collaboration Tools
CursorClaude CodeMiroGitHub MCPMicrosoft Power BI
Observability
DynatraceSplunk
Cloud & Principles
AWSTDDSOLIDMicroservicesEvent-Driven ArchitectureFault-Tolerant Design
Independent Work

Personal Projects

📡
Telemetry Streaming Pipeline

A real-time telemetry ingestion and processing pipeline that collects device and application metrics via Kafka, processes them through Spark Structured Streaming with windowed aggregations, and persists insights to PostgreSQL for monitoring dashboards and alerting.

PythonApache KafkaSpark StreamingPostgreSQL
Python
View on GitHub ↗
🗄️
node-express-postgres

A RESTful API service for banking account operations with fund transfer capabilities, transaction safety using foreign key constraints, and real-time balance tracking with PostgreSQL.

Node.jsExpressPostgreSQLREST API
JavaScript
View on GitHub ↗
🖥️
dynamic-screen-management

A configurable screen management system built with Node.js and Express, enabling dynamic routing and specification-driven UI rendering through a modular actions-based architecture.

Node.jsExpressJavaScriptOpenAPI
JavaScript
View on GitHub ↗
Academic Foundation

Academic Background

BNMIT, Bangalore
B.E. in Computer Science & Engineering
Aug 2014 – Jun 2018
CSE
Get in Touch

Open to Opportunities

Based in Bangalore, India · Open to remote & hybrid roles

Interested in data engineering, streaming systems & platform development

namputrev15@gmail.com

+91 94813 24896

LinkedIn ↗ Email ↗ Call ↗ GitHub ↗