Poonam Saini — Director of Engineering

• Data Engineer with 14 years of extensive experience in designing, building, and optimizing large-scale data architectures, pipelines, and infrastructure for high-impact, data-driven solutions. • Deep expertise in wide range of data technologies, including Hadoop, Spark ,NoSQL databases, and cloud platforms such as AWS. Proficient in Python, Scala, and other key programming languages essential for efficient data processing and ETL development. • Proven track record of creating and maintaining robust, scalable, and high-performance data ecosystems that support complex analytics, machine learning models, and real-time data processing, enabling businesses to extract actionable insights. • Experienced in leading data engineering teams, providing technical guidance, mentoring senior engineers, and fostering a culture of innovation and best practices. Adept at collaborating with data scientists, analysts, and business stakeholders to deliver end-to-end data solutions. • Expertise in optimising data workflows, ensuring data quality, security, and compliance, and implementing data governance frameworks that align with organisational goals. • Versatile professional with experience across various industries, including finance, retail, telecom, and e- commerce, consistently delivering data solutions that drive business growth, operational efficiency, and enhanced decision-making. • Passionate about leveraging the latest technologies and methodologies to continuously improve data infrastructure and stay ahead in a rapidly evolving data landscape. Committed to driving innovation and pushing the boundaries of data engineering. • Recognised for delivering data engineering solutions that have led to significant cost savings, revenue growth, and operational improvements, directly contributing to the success of the organisations.

Stackforce AI infers this person is a Data Engineering expert in Retail and E-commerce sectors.

Location: Gurgaon, Haryana, India

Experience: 15 yrs 7 mos

Skills

Data Engineering
Machine Learning
Data Analytics
Consumer Analytics
Supply Chain Management
Etl Development
Data Warehousing
Database Management

Career Highlights

14 years of experience in data engineering.
Expert in AWS, Hadoop, and Spark technologies.
Proven track record of optimizing data workflows.

Work Experience

ADIDAS INDIA MARKETING PRIVATE LIMITED

Director Data Engineering (1 yr 6 mos)

Senior Data Engineering Manager (5 yrs)

Paytm

Lead Data Engineer (3 yrs 4 mos)

CellOS Software Limited

Senior Software Engineer (3 yrs 10 mos)

Cognizant Technology Solutions

Programmer Analyst (1 yr)

Wipro Infotech Ltd

Software Engineer (2 yrs 5 mos)

Education

Master of Science (MS) at Birla Institute of Technology and Science, Pilani

Bachelor of Technology (BTech) at Punjab Technical University

Poonam Saini

Director of Engineering

Gurgaon, Haryana, India15 yrs 7 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

14 years of experience in data engineering.
Expert in AWS, Hadoop, and Spark technologies.
Proven track record of optimizing data workflows.

Stackforce AI infers this person is a Data Engineering expert in Retail and E-commerce sectors.

Contact

Skills

Core Skills

Data EngineeringMachine LearningData AnalyticsConsumer AnalyticsSupply Chain ManagementEtl DevelopmentData WarehousingDatabase Management

Other Skills

Amazon Web Services (AWS)PythonData VisualizationPower BIAWSData ForecastingApache AirflowSQLData ModelingApache Spark

About

Experience

15 yrs 7 mos

Total Experience

3 yrs 1 mo

Average Tenure

5 yrs

Current Experience

Adidas india marketing private limited

2 roles

Director Data Engineering

Promoted

Nov 2024 – Present · 1 yr 6 mos

Senior Data Engineering Manager

May 2021 – Present · 5 yrs

Retail Advanced Analytics: An analytical suite providing powerful set of applications designed to
transform data into actionable insights across critical business areas.
∗ Crafted automated store-level reporting with intuitive dashboards and visualisations, offering a comprehensive view of key metrics and KPIs.
∗ Leveraged cutting-edge machine learning algorithms to identify and mitigate fraudulent activities inside stores.
∗ Enabled historical data analysis to help uncover patterns and trends in fraudulent behaviour r enabling proactive risk management.
Scaled Consumer Engagement: A suite of Machine Learning and Power BI applications to under- stand the interactions with Consumers and Members. These meticulously crafted apps include Consumer Segmentation , Consumer & Membership Analysis and Campaign Analysis, each tailored to address dis- tinct facets of consumer engagement and insights.
∗ Leverage sophisticated machine learning algorithms to segment consumer base into distinct groups based on purchasing behaviour, demographics, and other key factors
∗ Streamlined reporting process with automated, scheduled reports that deliver consistent and up-to- date information directly to stakeholders
∗ Leverages advanced statistical methods and machine learning algorithms to automatically detect outliers, whether they represent errors, fraud, or rare events that warrant further investigation
Supply Optimisation: Ensuring sufficient stock is always available to meet expected demand. Buying & Planning need a trust-able recommendation tool, that provides a reliable, understandable forecast by bringing underlying information, and known limitations.
∗ Engineered & Optimised Rolling Demand Plan solution on AWS cloud platform (BDP), saving costs by 25%.
∗ Designed a global solution for EU market, easily scalable to other markets, reducing the Time to mar- ket by 40%.
∗ Architected platform agnostics solution foreseeing Databricks as new tech stack to be adopted company wide.

Amazon Web Services (AWS)PythonData EngineeringMachine Learning

Paytm

Lead Data Engineer

Jan 2018 – May 2021 · 3 yrs 4 mos · Noida Area, India

Responsible for integrating and maintaining new datasets to central warehouse, creating daily/weekly/- monthly aggregates, delivery of reports and dashboards.
◦ Architected Reconciliation Engine solution on which n sources can be reconciled by providing required configurations, reducing reconciliation efforts by 70%.
◦ Designed On demand Merchant Reporting solution, where merchants are served with in a defined SLA using this framework
◦ Migrated ETL framework of Python and Hive to PySpark (including daily runs, error handling, and log- ging) to clean useful data and create facts an OLAPs.

Amazon Web Services (AWS)Apache AirflowData EngineeringETL Development

Cellos software limited

Senior Software Engineer

Mar 2014 – Jan 2018 · 3 yrs 10 mos · Gurgaon, India

Designed multi-dimensional modelling (Star and Snowflake schemas) for data warehouse applications.
◦ Performed Source System Data analysis as per the Business Requirement. Distributed data residing in heterogeneous data sources is consolidated onto target Enterprise Data Warehouse database.
◦ Worked closely with the business users to understand the requirements and converting them into project level technical capabilities.

PythonSQLData EngineeringData Warehousing

Cognizant technology solutions

Programmer Analyst

Feb 2013 – Feb 2014 · 1 yr · Gurgaon, India

Analyzed the sources, targets, transforming and mapping the data and loading the data into targets.
∗ Involved in extraction of data from the different flat files and data from Oracle OLTP Systems.
∗ Developed ETL transformations, mappings, sessions and workflows.
∗ Created Slowly Changing Dimension (SCD) Type 2 mappings for developing the dimensions to main-
tain the complete historical data.

SQLData ModelingData EngineeringETL Development

Wipro infotech ltd

Software Engineer

Aug 2010 – Jan 2013 · 2 yrs 5 mos · Gurgaon, India · On-site

Created, optimized, reviewed, and executed Teradata SQL test queries to validate transformation rules used in source to target mappings/source views, and to verify data in target tables.
∗ Performed tuning and optimization of complex SQL queries using Teradata Explain.
∗ Performance Tuning of sources, Targets, mappings and SQL queries in transformations designing, creating and tuning physical database objects (tables, views, indexes, PPI, UPI, NUPI, and USI) to
support normalized and dimensional models.
∗ Created proper Primary Index taking into consideration of both planned access of data and even dis-
tribution of data across all the available AMPS.
∗ Configured the mappings to implement Slowly Changing Dimensions (Type-2).

SQLData ModelingData EngineeringDatabase Management