Sambit Mohanty

Enterprise Data Engineering & Platform Leader with 22+ years of experience building and transforming large-scale data ecosystems within a Fortune 50 environment. Lead globally distributed engineering organizations of up to 40 engineers, including engineering leads, with responsibility for enterprise data platforms operating at approximately 5 PB scale, processing ~8 TB of daily data movement, 4,000+ data pipelines per day, and 1M+ analytical queries daily. Influence approximately $25M in annual cloud and data-platform investment across GCP and enterprise semantic capabilities.

Partner with VP-level business, product, architecture, and technology leaders to drive data strategy, cloud modernization, platform engineering, governance, engineering excellence, and AI-ready data capabilities across merchandising, supply chain, and partner ecosystems.

Senior Engineering Manager – Data Engineering at TARGET CORPORATION (2016-07 – Present)

• Lead a 25-member globally distributed Data Engineering organization across India and the US, managing 4 engineering leads and having led organizations of up to 40 engineers across enterprise data and platform initiatives.
• Provide engineering leadership across an enterprise analytical data ecosystem operating at approximately 5 PB scale, with ~8 TB of daily data movement, 4,000+ data pipelines/day, and 1M+ analytical queries/day.
• Own 300+ certified enterprise datasets on GCP while providing technical strategy and consultation across a broader data ecosystem spanning 1,500+ certified data assets, 5,000+ data pipelines, 1,000+ metrics, and 50K dashboards.
• Influence approximately $25M in annual cloud and data-platform investment across GCP and enterprise semantic capabilities, partnering with senior leadership on platform strategy, modernization, capacity, and cost optimization.
• Lead enterprise data platforms supporting 3,000+ external business partners and high-volume business-critical data exchange.
• Define and drive enterprise Data Engineering strategy and technology roadmaps, aligning cloud-native platform investments with long-term business and technology priorities.
• Partner with VP-level business, product, architecture, and digital leaders to influence technology investments, platform modernization, engineering standards, and enterprise data capabilities.
• Led enterprise semantic-layer technology evaluation and vendor engagement, assessing AtScale, Cube Cloud, and Kyvos against Target's analytical and data-platform requirements.
• Led a Proof of Concept (POC) using Looker and LookML, validating the semantic-model approach and contributing to the selection of Looker/LookML for Target's semantic capabilities.
• Drive engineering excellence through architecture governance, reusable platform capabilities, DataOps, observability, data quality, automation, and engineering standards.
• Provide technical and organizational leadership across complex enterprise data initiatives spanning Merchandising, Supply Chain, Vendor/Partner, Owned Brands, and enterprise analytics.
• Led enterprise-scale modernization from legacy/Hadoop ecosystems to GCP-native data platforms, with the team directly migrating approximately 400 data pipelines to the modern cloud platform.
• Conceived and developed an AI-assisted migration framework and automation tool to accelerate migration of the broader ecosystem of approximately 1,500 data pipelines, standardizing migration patterns and reducing manual engineering effort at enterprise scale.
• Improved average data-processing time from approximately 1.2 hours to 25 minutes, delivering a ~65% reduction in processing time and enabling faster availability of business-critical data.
• Directed modernization across a multi-petabyte analytical ecosystem, establishing cloud-native architecture, reusable engineering patterns, automated data-quality controls, observability, and platform governance.
• Architected and scaled batch and streaming capabilities using BigQuery, Dataproc, Dataflow, Apache Spark, Scala, Kafka, and GCP-native services.
• Established DataOps, CI/CD, reusable engineering frameworks, automated testing, and deployment standards, reducing deployment time by approximately 40% and enabling 3× faster release cycles.
• Drove adoption of AI-assisted engineering practices using GitHub Copilot, Claude, GPT-based tools, and related capabilities, accelerating applicable data-pipeline development workflows by approximately 50%.
• Strengthened platform reliability through automated data quality, observability, SLA monitoring, and engineering controls, contributing to approximately 30% fewer production incidents.
• Championed platform standardization, reusable engineering capabilities, automation, and cloud cost optimization across enterprise data initiatives.
• Built and scaled enterprise Merchandising and Supply Chain Data Platforms, delivering 300+ certified data products that improved access to trusted, timely data for merchandising, inventory, and supply-chain decision-making.
• Led the Business Partner Data Platform supporting 3,000+ external vendors and partners, establishing scalable and governed data capabilities for critical partner-facing business processes.
• Co-developed the enterprise Signals platform, enabling data-driven anomaly and fraud detection across large-scale business datasets.
• Established trusted enterprise data foundations across Item, Vendor, Promotion, Sales, Supply Chain, and Partner domains, enabling analytics and operational decision-making across critical retail functions.
• Built and scaled high-performing engineering organizations through strategic hiring, large-scale recruitment initiatives, leadership development, coaching, and succession planning.
• Lead through 4 engineering leads, developing senior engineers and emerging leaders while creating organizational capacity for enterprise-scale data initiatives.
• Mentored engineers and technical leaders through career progression and promotion while developing succession pipelines for critical engineering roles.
• Built and evolved engineering teams of up to 40 members, aligning organizational structure and technical capabilities with long-term platform and transformation priorities.
• Sustained 95–98% employee engagement scores through strong engineering culture, career development, inclusive leadership, and team empowerment.

Engineering Manager – Supply Chain Engineering at TARGET CORPORATION (2014-07 – 2016-06)

• Led the enterprise supply-chain modernization program for the DPM application, driving the IBM Zero Initiative by migrating legacy IBM WebSphere-based applications to open-source, containerized Spring Boot, Apache Tomcat, and Docker architectures.
• Directed a multi-year technology transformation supporting 100+ Distribution Centers, Regional Distribution Centers, and Fulfillment Distribution Centers, improving application portability, deployment efficiency, scalability, and infrastructure optimization.
• Partnered with technology, enterprise architecture, product management, and business stakeholders to define and execute modernization roadmaps while maintaining uninterrupted support for critical supply-chain applications.
• Built and scaled high-performing engineering teams through strategic hiring, talent development, mentoring, and alignment of technical capabilities with long-term transformation objectives.
• Established engineering practices across application modernization, CI/CD, DevOps, automation, resiliency, performance optimization, and production operations.

Sr. Engineer / Project Leader / Project Manager – Data Engineering at TARGET CORPORATION (2007-10 – 2014-06)

• Built and scaled enterprise ETL/ELT frameworks, standardizing data ingestion, transformation, and delivery across multiple retail business domains.
• Established enterprise data platforms for Merchandise Item and Vendor domains from the ground up, creating trusted data foundations for merchandising and enterprise analytics.
• Designed enterprise data quality, validation, reconciliation, and automated testing frameworks, improving data reliability and reducing production defects.
• Partnered with business stakeholders, product teams, and enterprise architects to define data requirements, prioritize delivery roadmaps, and deliver analytics-ready data products.
• Successfully transitioned enterprise Data Engineering capabilities from the US to India, establishing delivery processes, governance standards, knowledge transfer, and offshore engineering capability.
• Led cross-functional engineering teams through end-to-end program delivery, ensuring stakeholder alignment, engineering quality, and execution.

Software Engineer at INFOSYS (2004 – 2007)

• Developed enterprise Java applications and data-integration solutions.
• Designed ETL and Data Warehousing solutions supporting enterprise reporting.

Executive General Management Program – Indian Institute of Management Bangalore

Bachelor of Technology – College of Engineering and Technology, Bhubaneswar