Priya Yadav

Junior Analytics Engineer

Salaire / Taux journalier

Choisy-le-Roi, France

Freelance, ouvert au CDI

Peut venir sur site

Expertises

AWSdbtPythonTableauEvent Driven ArchitectureData MiningETLScrapingData EngineeringC++RAzurePower BIGitGitLabGoogle Cloud PlatformSnowflakeDockerKafkaDatabricksShopifyProduct MarketingData AnalysisMachine LearningWebflowScrumConfluenceJiraWordPressGoogle AnalyticsA/B testingWeb AnalyticsAirtableRequêtes SQL

Langues

AnglaisHindiFrançais

À propos

Introduction

Analytics Engineer with 3+ years of experience designing scalable ELT/ETL pipelines, developing dbt models, and orchestrating data workflows with Airflow and Azure Data Factory. Skilled in cloud data warehousing (AWS Redshift, GCP, Azure), data modeling, and BI tools (Tableau, Power BI, HEX). Experienced in containerized development environments using Docker. Adept at building reliable, production-grade data systems with automated testing, CI/CD, and anomaly detection using dbt and Datafold.

Liens

Expérience de travail

Stonly

nov. 2023 - Présent

3 ans

Paris, France

Junior Analytics Engineer

juin 2024 - Présent

2 ans 5 mois

Paris, France

Owned end-to-end analytics pipelines, from raw ingestion to modeling (staging, incremental, intermediate, mart, fact, dimension, and snapshot layers), ensuring high-performance, reliable reporting across Sales, Marketing, Finance, and Product teams. Integrated Salesforce CRM with Redshift and automated data sync, enabling near real-time reporting and loading transformed data back into Salesforce/ticketing systems for operational use. Containerized dbt and Airflow environments using Docker for consistent development, faster deployment, and smoother collaboration across the data team. Automated ELT/ETL workflows with dbt, Airflow, and AWS Glue, including validation, anomaly detection, and backfilling processes to ensure production-grade data quality. Implemented full CI/CD pipelines integrating dbt Cloud, Git, Slack alerts, Datafold, and Airflow checks for continuous testing and proactive failure detection. Delivered strategic insights on customer segmentation, churn, retention, and revenue trends, directly supporting Series B funding decisions and key business initiatives. Created interactive KPI dashboards in HEX and Tableau for both internal teams and external customers, giving them clear, reliable visibility into key business metrics.

Data Analytics Engineer Intern

nov. 2023 - juil. 2024

9 mois

Paris, France

Data Analyst

Raina

juil. 2019 - juil. 2021

2 ans 1 mois

Indianapolis, Indiana, États-Unis

Partner with marketing, sales, customer success teams and other stakeholders to create and deliver ad hoc requests, ongoing business insights and customer analysis from data stored on cloud, using SQL and python Leveraged marketing data to forecast marketing campaign success and sales trends Create and manage recurring data collection, analysis, and reporting used by sales and marketing teams to measure, analyze, and understand KPIs, areas of concern and opportunities for improvement Collaborated with marketing, product management, and sales to establish value propositions for new and existing products. Built dashboards to monitor business metrics using Tableau and Mode. Identified potential markets and market segments with desired customers and gaps for optimum product demand. Developed and implemented process improvements resulting in 2.7% increase in productivity. Leverage data mining methodologies to extract actionable insights from expansive datasets and drive informed business decisions

Analyst Intern

SHREE FAB

sept. 2018 - déc. 2018

4 mois

Indianapolis, Indiana, États-Unis

Collaborated with UI/UX team to monitor user site behavior and set up A/B tests to help optimize the website Engineered web-scrappers for collecting product data and data pipelines for ingestion and integration to extend the product database and improve analysis and reporting - resulting in reduced cost of products and increased acquisition of customers Collaborated with sales and marketing team and utilized data for trend (lead time) analysis and modeling of customer needs and behavior, resulting in improved demand forecasting and superior user engagement.


Formation

IÉSEG School of Management

Master of Science - MS

2022 - 2024

1 an 10 mois

Gujarat Technological University (GTU)

Bachelor of Science - BS

2013 - 2017

3 ans 10 mois

Le meilleur endroit pour trouver votre prochaine opportunité

© 2026. Tous droits réservés.