Anuj Shrivastav
Lead Data Engineer- Data & Analytics @PepsiCo
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WORK HISTORY
Lead Data Engineer- Data & Analytics @PepsiCo
Hyderabad, IN
Leading a team of 6 Data Engineers to modernize PepsiCo Europe’s data platform under the Modern Data Intelligence Program (MDIP), leveraging Azure Data Factory (ADF), Azure Databricks, and ADLS Gen2 to enable scalable analytics and faster business decision-making.Designed and orchestrated daily DIM & FACT data loads using ADF pipelines integrated with Databricks notebooks for large-scale Spark transformations across Bronze, Silver, and Gold layers. Built a robust and scalable data architecture to support reliable batch processing and enterprise reporting.Collaborated closely with business stakeholders to translate requirements into data-driven solutions aligned with strategic objectives. Led technical discussions and guided development teams on architectural best practices and implementation standards.Implemented performance optimization across data pipelines and ETL workflows by tuning Spark configurations, enhancing Delta Lake operations, resolving small-file issues, and optimizing job scheduling to meet SLA requirements.
EDUCATION
AppliedRoots & Applied AI Course
Applied Machine Learning Online Course
Shri Shankaracharya Technical Campus
Computer Science and Engineering, Computer Software Engineering
ABOUT ANUJ SHRIVASTAV
PepsiCo Leading a team of 6 Data Engineers to modernize PepsiCo Europe’s data platform under the Modern Data Intelligence Program (MDIP). I drive scalable, cloud-native data solutions using Azure Data Factory (ADF), Azure Databricks, and ADLS Gen2 enabling advanced analytics and faster, data-driven decision-making at enterprise scale.With strong expertise in modern data engineering ecosystems, I specialize in: Azure Stack: ADLS Gen2, Azure Databricks, Synapse, Azure Data Factory Big Data Processing: Apache Spark, Hadoop Lakehouse Architecture: Bronze → Silver → Gold layers with Delta Lake optimization Pipeline Engineering: Reliable, automated ETL/ELT workflows Performance Tuning: Partitioning strategies, OPTIMIZE/Z-ORDER, small-file optimization Programming: SQL, PythonI focus on building cost-efficient, SLA-driven, high-performance data platforms that scale with business growth.Passionate about transforming raw data into actionable intelligence that drives measurable business impact Open to networking, collaborations, and discussions around Data Engineering, Lakehouse Architecture, and Cloud Analytics.
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