Anuradha Jha

Backend Engineer

West Delhi, Delhi, India4 yrs 6 mos experience

Highly Stable

Key Highlights

Expert in backend development and cloud migration.
Proven track record in enhancing user engagement.
Strong analytical skills with a focus on data quality.

Stackforce AI infers this person is a Backend-focused SaaS engineer with expertise in cloud technologies and data engineering.

Contact

Skills

Core Skills

Node.jsAwsPythonDatabasesOpenstackAirflowKubernetes

Other Skills

Amazon Web Services (AWS)Analytical SkillsApache SparkBloggingBoto3C (Programming Language)C++Cloud FunctionsDAGData AnalysisElasticsearchExpress.jsFFmpegFfmpegFirebase

About

Tech generalist

Experience

Animall

Backend Engineer

Sep 2021 – Apr 2025 · 3 yrs 7 mos · Bangalore Urban, Karnataka, India · On-site

Enhanced content quality by 15% by providing listings through a geolocation-based feed algorithm using GraphHopper and Redis
Automated cattle assessment for 7 insurance companies by developing an assessment framework using TensorFlow and Razorpay
Accelerated buyer activation by 5% through developing & integrating search and filter algorithms using Elasticsearch & MongoDB
Amplified the platform's reach through direct messaging and notifications for users by 15% through integrating WhatsApp APIs
Collaborated on the migration of entire infra from GCP to AWS with 30% less cost and no up-time hindrance for the end users
Boosted platform's user engagement by 17% through implementing thumbnail generation using FFmpeg and Cloud Functions

DatabasesJavaScriptNode jsRedisMongoDBMySQL+16

Outreachy

Intern - Openstack(OpenInfra Foundation)

Dec 2020 – Mar 2021 · 3 mos · New York, United States · Remote

Improved the bootstrapping bare metal deployment reliability of Ironic API on OpenStack SDK by integrating Unit & Function tests
Collaborated with system engineers at CERN and RedHat, contributing to the release of the stable version of Ironic used internally

OpenStackAnalytical SkillsPythonGitRed Hat LinuxShell Scripting+1

Atlan

Data Engineer

Jan 2020 – Dec 2020 · 11 mos · New Delhi, Delhi, India · On-site

Reduced cost by 10% & prevented DAGs cascading failures by developing event-based triggers and circuit breakers using Python operators in Airflow
Improved data accuracy by 60% by implementing Data Quality checks to remove anomalies across interconnected DAGs using Kubernetes & Airflow
Reduced failure resolution time by 50% by developing an internal tool to analyze dependencies & relationships within Airflow DAGs using NetworkX
Boosted user retention by 20% by designing a compact internal tool to track product metrics, facilitating user adoption and engagement using Python
Expedited product launch from POC to final stage in a month by migrating customers' business workflows from Sheets by using Python and SQL
Onboarded 2 clients for POC and made the product cloud-agnostic by adding compatibility for Azure through migration from Boto3 to smart-open

KubernetesPython (Programming Language)Analytical SkillsNetworkXPythonSQL+6