---
title: "Ashish Kumar - Data Engineer in Bengaluru | Tal"
description: "Meet Ashish Kumar, Data Engineer @ Zepto | Real-Time Streaming & Batch Pipelines | Kafka · Flink · Spark · Databricks · AWS | Ex-Nielsen · Ex-Tredence | based in Bengaluru. AI stack includes claude code, claude, and codex."
image: "https://tal.club/meet/ashish-kumar-49/share-image"
---

# Ashish Kumar on Tal

## Headline

Data Engineer @ Zepto \| Real\-Time Streaming & Batch Pipelines \| Kafka · Flink · Spark · Databricks · AWS \| Ex\-Nielsen · Ex\-Tredence \|

## About

I build data systems that businesses can't afford to have go down\. Over 4 years, I've engineered large\-scale data platforms across Quick Commerce, Audience Measurement and CPG domain— powering supply chain planning, real\-time inventory intelligence, and operational decision\-making at Zepto, Nielsen, and Tredence\. At Zepto today, I own the Planning data platform driving automated replenishment across 1200\+ dark stores, every SKU, every minute\. What I've shipped: Architected a real\-time Inventory Tracking System — Kafka event backbone → Flink stateful streaming → ClickHouse OLAP — replacing a 30\-min stale batch job with sub\-second stock queries Built an IaaC job management framework in Pyspark \+ GitHub Actions governing 200\+ Databricks jobs, eliminating 100% of manual overhead and cutting onboarding from days to under 2 hours Engineered an Anomaly Detection System \(Pyspark\+ Z\-score \+ Redis baseline caching \+ Delta Lake telemetry\) that reduced pipeline incidents by 50% and MTTR from 90 → 30 minutes Delivered a Data Quality & Schema Governance Framework that saved engineers 3–4 hours per incident across gold\-layer planning tables Achieved a 4\.5× query speedup and 10–15% Databricks cost reduction through system\-wide Spark optimisation Generated $200K in client revenue at Tredence via a Python XML parser that automated data discovery for Fortune 500 onboarding Stack I work with: Streaming & Batch: Kafka · Flink \(PyFlink\) · PySpark · Spark SQL · Airflow Storage & Warehousing: ClickHouse · Delta Lake · Snowflake · Redshift · S3 Cloud: AWS \(primary\) · Azure · Databricks Reliability: Redis · Anomaly Detection · Data Quality Frameworks · CI/CD · GitHub Actions Domains: Quick Commerce · Supply Chain Planning · Inventory Intelligence · CPG Certifications: Gen AI Fundamentals · Databricks Certified Data Engineer Associate · SnowPro Core · Azure DP\-900 📩 Let's connect if you're building fast data systems or tackling ops at scale\. 📊 Book a 1:1 session: topmate\.io/ashish\_kumar\_de

## Location

Bengaluru

## AI stack

claude code

claude

codex

cursor

gemini

grok

## Work experience

Data Engineer at Zepto, Mar 2025 \- Present · 1 yr 7 mos, Bengaluru, Karnataka, India, Own Zepto's Planning data platform driving automated replenishment across FMCG, SuperStore, Cafe & Milk supply chains for 1100\+ dark stores\. Architected real\-time Inventory Tracking System \(Kafka → Flink → ClickHouse\) replacing 30\-min batch staleness with sub\-second stock queries Built PR\-based IaaC framework governing 200\+ Databricks jobs — eliminated 100% manual tracking, cut onboarding from days to 2 hours Engineered Anomaly Detection System \(Z\-score \+ Redis \+ Delta Lake\) — 50% fewer incidents, MTTR 90 → 30 min Re\-architected FMCG pipelines in PySpark — 4\.5× query speedup, 10–15% Databricks cost reduction, 40\+ GB memory freed Built Data Quality & Schema Governance Framework — saved 3–4 hrs/incident across gold\-layer planning tables Kafka · Flink · PySpark · Databricks · ClickHouse · Redis · Airflow · Delta Lake · S3

Data Engineer II at Nielsen, Sep 2024 \- Feb 2025 · 6 mos, Bengaluru, Karnataka, India, Refactored and optimised ELT pipelines for Nielsen's TV audience measurement platform processing 2M\+ records daily\. Resolved 20% processing bottleneck via broadcast joins, salting, and multi\-threading on S3\-backed Spark clusters Improved end\-to\-end efficiency by 30% through SQL predicate pushdown and materialised Parquet intermediate layers

Data Engineering Consultant at Tredence Inc\., Jan 2024 \- Aug 2024 · 8 mos, Bengaluru, Karnataka, India · Hybrid, Delivered data engineering across Fortune 500 engagements — cloud migration, pipeline optimisation, and automated tooling\. Built Python XML parser cutting discovery time 25%, generating $200K in new revenue Migrated IBM DataStage pipelines to ADF \+ ADLS Gen2 \+ Databricks — 20% faster processing, full Azure Monitor observability Tuned PySpark on AWS EMR across 15 TB / 12B records — replaced UDFs with Spark SQL window functions, 20% runtime improvement Designed star\-schema models in Hive and Snowflake supporting BI and self\-service analytics PySpark · AWS EMR · Azure Data Factory · Databricks · Snowflake · Hive · Delta Lake

Analyst \- Data Engineer at Tredence Inc\., Jun 2022 \- Dec 2023 · 1 yr 7 mos, Bengaluru, Karnataka, India · Hybrid, Started as a campus hire, ramped quickly into production data engineering across AWS, Azure, and GCP client engagements\. Built and maintained ETL pipelines ingesting from AWS S3/Glue, Azure ADLS, GCP GCS, Oracle, and SFTP across JSON, CSV, and Parquet formats Performed deep\-dive SQL and Spark SQL analysis to resolve SIT/UAT defects and maintain production stability Promoted to Data Engineering Consultant within 18 months based on delivery impact Python · SQL · PySpark · Spark SQL · AWS · Azure · JIRA

Training & Placement Representative at Centre of Training & Placement,NIT Jalandhar, Sep 2020 \- Jun 2022 · 1 yr 10 mos, Jalandhar, Punjab, India

## Education

Bachelor of Technology \- BTech, Chemical Engineering, Dr B R Ambedkar National Institute of Technology, Jalandhar

Senior Secondary \| CBSE, Adarsh Vikas Vidyalaya

[View the original profile](https://tal.club/meet/ashish-kumar-49)

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