Manideep Ganji

Dynamic and results-driven Data Engineer with a robust background in Big Data Technologies, seeking to leverage expertise in data engineering and analytics to drive organizational growth and innovation within the IT sector. Data Engineering professional with nearly 7 years of experience in Big Data, Databricks, GCP, and GenAI technologies. Seeking opportunities in Data Engineering and Cloud Data Engineering to leverage expertise in building scalable data platforms, modern data pipelines, and cloud-based analytics solutions.

Directed payments and finance transformation initiatives, driving revenue growth, operational efficiency, financial governance, and scalable transaction ecosystems across complex business environments. Partnered with business, product, technology, and banking stakeholders to deliver data-driven financial strategies, optimize unit economics, improve profitability, and strengthen working capital performance. Built and mentored high-performing teams, championing automation, process excellence, and robust control frameworks to enhance operational resilience, audit readiness, and sustainable business growth.

Proficient in leveraging Azure and AWS to support cloud-based data engineering, analytics, and scalable data solutions.

Senior Data Engineer at Fractal Analytics (2024-01 – Present)

• Spearheading the design and delivery of scalable Databricks and Spark-based data platforms, enabling enterprise-grade analytics capabilities for a leading global CPG organization.
• Architecting cloud-native data warehouse solutions on BigQuery and Google Cloud Storage, establishing a robust foundation for high-volume data ingestion, governance, and reporting.
• Accelerating development productivity by integrating AI-driven engineering practices and quality frameworks, achieving reduction in development effort while consistently meeting SonarQube compliance standards.
• Directing the successful execution of a strategic AMEA transformation program across 5 international markets, ensuring seamless deployment, stabilization, and ongoing production support.
• Orchestrating cross-functional collaboration among Data Science, Data Ingestion, DevOps, and external partner teams to align technical delivery with business priorities and drive stakeholder outcomes.
• Mentoring junior engineers and assumed expanded responsibilities across MLOps, project governance, and solution architecture, strengthening team capability and supporting delivery within a key revenue-generating account.

Senior Data Engineer at Quantiphi Analytics (2022-09 – 2023-12)

• Led the modernization of enterprise data platforms by migrating on-premises PySpark batch workloads to GCP Dataproc and orchestrating them through Cloud Composer, significantly enhancing scalability, scheduling, and operational monitoring.
• Architected and deployed real-time data processing solutions on Google Kubernetes Engine (GKE) using Docker-based streaming applications, enabling faster ingestion, processing, and analytics of business-critical data.
• Engineered end-to-end ETL frameworks leveraging Dataflow, BigQuery, and external APIs, strengthening data integration capabilities and accelerating data availability for downstream analytics and reporting.
• Directed a cross-functional team of 8 data engineering professionals on a large-scale transformation program, ensuring timely delivery, technical excellence, and alignment with client objectives.
• Optimized software delivery processes through robust GitHub, CI/CD, unit testing, integration testing, and data validation frameworks, improving deployment reliability and ensuring high data quality standards.
• Spearheaded the successful migration and refactoring of on-premises batch and streaming workloads to Google Cloud Platform for a Fortune 500 client, driving improved scalability, operational efficiency, and cloud cost optimization while strengthening long-term client partnerships.

Data Engineer at Loctruth (Product Based Bootstrapped Startup) (2020-10 – 2022-09)

• Engineered a high-scale geospatial data platform processing millions to billions of time-series records daily, enabling fast, reliable ingestion, storage, and analytics for location intelligence use cases.
• Developed and maintained business-critical insight datasets while implementing data quality frameworks, improving data reliability and accelerating analytics-driven decision-making.
• Automated clustering and trend-analysis models to identify location-based behavioral patterns, enhancing customer segmentation accuracy and targeted marketing effectiveness.
• Architected scalable APIs, CDP integrations, and custom geolocation audience solutions while managing the end-to-end data engineering lifecycle, improving data accessibility, operational efficiency, and campaign performance.

Data Engineer at Reliance Industries Limited (2019-06 – 2020-05)

• Collaborated with business and analytics stakeholders to translate complex requirements into scalable big data solutions, ensuring alignment between operational objectives and technology deliverables.
• Leveraged Hadoop ecosystem technologies including Hive, Sqoop, Spark, and HDFS to process and analyze large-scale datasets, improving data accessibility and accelerating insight generation.
• Engineered optimized ETL and data integration frameworks using Spark SQL, Scala, and Sqoop, streamlining data movement between HDFS and relational databases while enhancing processing efficiency.
• Transformed raw enterprise data into actionable business insights through advanced data cleansing, integration, and analytical workflows, contributing to improved reporting accuracy and decision-making effectiveness.

Masters in Computer Science Engineering (Big Data Analytics) – VIT, Vellore (2020)

Bachelors in Electronics and Computer Engineering – JNTUH (2018)