Rohan Ojha

Senior Software Engineer

Mumbai, Maharashtra, India4 yrs 9 mos experience

Key Highlights

Drove $48M revenue uplift through data analytics.
Improved data accuracy by 95% with automated frameworks.
Reduced time-to-deploy for data products by 40%.

Stackforce AI infers this person is a Big Data and Azure specialist with strong SaaS experience.

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Skills

Core Skills

Big DataAzureData Analytics

Other Skills

API IngestionAlgorithmsAnacondaApache SparkApache Spark StreamingApache SqoopAutomationAzure Analysis ServicesAzure Data LakeAzure DataFactoryAzure DataLakeAzure DatabricksAzure Key VaultAzure Logic AppsAzure Synapse Analytics

About

> Programming Language :- Core JAVA, Python and Scala > Big Data Technologies :- Hadoop , Map Reduce, HDFS , Hive, Sqoop and Apache Spark (Pyspark). > (Microsoft Azure) :- Azure DataFactory , Azure Databricks ,Azure DataLake ,Azure Key Vault, Azure Logic Apps and Azure Analysis Services. > Databases :- Oracle 8i, 9i, 10g, 11g and MYSQL and Cassendra. > IT Construct :- Data Structures and Algorithms ,Multithreading and Concurency Control , Distributed Systems, Apache Kafka .

Experience

4 yrs 9 mos

Total Experience

2 yrs 9 mos

Average Tenure

2 yrs

Current Experience

Tiger analytics

Senior Software Engineer - Big Data

May 2024 – Present · 2 yrs · Bengaluru, Karnataka, India · Remote

Part of Activation team at Mars USA Pet Care handling diverse data source of data api by building transforming and optimising their product using Azure big data technology
i. Design and devloped end to end unified data analytics platorm for one of its key retailers of mars by integrating over 2 TB/month of marketing performance data from Amazon Ads API and building core KPI tracking around key kpis ; drove ~35% increase in ad efficiency and supported a YoY revenue uplift of $48M, empowering digital marketing and category teams with real-time spend vs ROI insights.
ii. Designed and built an end-to-end data pipeline to deliver a proof-of-concept sales trend analytics report for one of its key retailer, analyzing in-store performance data across 10,000+ North American locations to measure the impact of bi-monthly discount campaigns within a 5-mile competitive radius. Implemented logic to identify best- and least-selling items using historical sales comparisons and geospatial mapping , enabling business teams to correlate campaign timing with profit lift. The insights drove a 14% increase in category-level sales, informed future production planning and stocking decisions, and laid the foundation to scale similar campaign analysis across other major retailers in Mars’ optimization roadmap.
iii. Developed a reusable PySpark framework for data transformation and KPI computation across sales, marketing, inventory and forecast domains, reducing time-to-deploy for new data products by 40%, improving data consistency, and enabling faster rollout of reporting solutions across cross-functional business teams.
iv. Spearheaded the transition to a unified Azure-based data lake architecture for Mars Petcare’s North America operations, integrating siloed datasets across retail, marketing, and sales- inventory, significantly reducing data duplication and powering real-time dashboards accessed by over 150+ users, handling a data volume of 5+ TB/month.

Azure DataFactoryAzure DatabricksAzure DataLakeAzure Key VaultAzure Logic AppsAzure Analysis Services+6

Infosys

Specialist Programmer - Big Data

Aug 2021 – May 2024 · 2 yrs 9 mos · Bengaluru, Karnataka, India · Remote

Cleared Hackwithinfy 2020 Coding Competition conducted by Infosys PAN India and got selected as Power Programmer role.
Part of Professional Service Data and Insights Engineering Team at Microsoft Building Transforming and Optimizing their Platform using Azure Big Data Technology.
Contributed to building Microsoft’s Professional Service Data Platform end-to-end, enabling BI & analytics solutions that supported global consulting and enterprise services designed 20+ foundational capabilities for modern data lake platform which supports all data and insights needs for Microsoft $8BN business with over 14K + Customers ,30K+ Users across 50+ Business Personas with data size of ~ 1.2 PB.
Improved processing efficiency of financial and operational datasets by 40%, reducing compute costs by 25% through Spark job optimization.
Accelerated report refresh cycles by 70% by migrating Analysis Services Cubes from ADLS Gen1 to Gen2, enhancing reporting experience for 500+ enterprise users.
Strengthened trust in analytics by improving data accuracy by 95% through automated validation frameworks and proactive data quality checks.
Delivered 15+ new business-facing features at PSDL platform and managed around 30+ Important KPIs for Value Based Delivery Insights with customers attendance around 50K + across the globe by improving adoption of self-service analytics and accelerating decision-making for stakeholders on this.
Implemented proactive monitoring and alerting frameworks, ensuring 93.9% pipeline availability and minimising downtime for critical business operations.
Automated finance reporting pipelines on PSDL, unlocking $3M+ annual savings by eliminating manual processes and reducing reporting cycle times.
Supported multi-billion-dollar Microsoft business units with data-driven insights from PSDL, contributing to enterprise-wide cloud adoption and revenue growth initiatives.