Headline

Data Leader

About

Solution-driven Data Engineering Manager with over 10 years of experience in data engineering, data science, and reporting. I specialize in building scalable data pipelines, optimizing infrastructure, and delivering insights for enterprise-level clients. Here’s a quick overview of my professional expertise: • Extensive Experience: Over a decade in data engineering and data science, with a focus on scalable data architecture, machine learning models, and analytics. • Cloud Expertise: In-depth experience in cloud platforms (Google Cloud and AWS), building and optimizing data pipelines to improve performance and reduce operational costs. • Data Strategy Leadership: Led the strategic design and execution of data platforms that directly aligned with business goals, resulting in operational efficiencies and better decision-making. • Advanced Analytics & Machine Learning: Implemented machine learning models and advanced analytics techniques, driving business insights and enhancing user engagement. • Cross-Functional Collaboration: Proven ability to work with product, engineering, and data science teams to deliver actionable solutions using Agile methodologies. • Optimized Pipelines & Governance: Expertise in developing optimized data pipelines and ensuring robust data governance practices, leading to enhanced data security and compliance. • Leadership & Mentorship: Experienced in leading large teams, mentoring engineers, and fostering collaboration across technical and non-technical stakeholders.

Location

Bengaluru

AI stack

anthropic apis

claude code

codex

cursor

hugging face

huggingface

Work experience

Engineering Manager at 6sense, Jun 2025 - Present · 1 yr 3 mos, Bengaluru, Karnataka, India

Engineering Manager - Data at Noice, Jun 2022 - Jul 2025 · 3 yrs 2 mos, India, 𝗦𝘂𝗺𝗺𝗮𝗿𝘆: As Engineering Manager at NOICE, I lead the development and optimization of large-scale data platforms. I focus on real-time, low-latency data pipelines while overseeing the migration of infrastructure to the cloud, improving efficiency, reducing operational costs, and enhancing user engagement through machine learning integration. I also drive data strategy initiatives to align technical objectives with business goals and mentor a team of engineers. 𝐒𝐤𝐢𝐥𝐥𝐬: • 𝐃𝐚𝐭𝐚 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬: Cloud migration, real-time data processing • 𝐂𝐥𝐨𝐮𝐝 𝐓𝐨𝐨𝐥𝐬: Google Cloud Platform (GCP), AWS, Terraform • 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: Python, SQL • 𝐌𝐋/𝐀𝐈: Generative AI, Large Language Models (LLMs), Machine Learning • 𝐃𝐚𝐭𝐚 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞: Security frameworks, data privacy compliance • 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩: Team management, cross-functional collaboration • 𝐑𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐓𝐨𝐨𝐥𝐬: Tableau, Data Studio 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: • Managed real-time data platforms, ensuring high throughput and low latency across all data pipelines. • Led cloud migration to GCP and AWS, cutting pipeline processing times by 40%. • Collaborated with product and ML teams to develop data-driven features, increasing user engagement. • Reduced operational costs by 25% by automating data workflows and optimizing infrastructure. • Implemented advanced machine learning models (including LLMs and Generative AI) to enhance platform performance. • Designed a new data governance framework that improved compliance and security across the platform. • Led quarterly data strategy sessions with C-suite executives to align data projects with business objectives.

Senior Data Engineer at KAR Global, Oct 2021 - Jun 2022 · 9 mos, Chicago, Illinois, United States, 𝐒𝐮𝐦𝐦𝐚𝐫𝐲: As Senior Data Engineer at KAR Global, I was responsible for migrating and optimizing our data warehouse systems, leading the integration of Snowflake, refactoring ETL processes, and automating data pipelines. I also worked with AWS services to enhance system efficiency, reduce costs, and support analytics and reporting for the business. 𝐒𝐤𝐢𝐥𝐥𝐬: • 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐢𝐧𝐠: Snowflake, Redshift • 𝐄𝐓𝐋 & 𝐃𝐚𝐭𝐚 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧: Apache Airflow, AWS Glue • 𝐂𝐥𝐨𝐮𝐝 𝐓𝐨𝐨𝐥𝐬: AWS (MWAA, S3, ECS, EKS) • 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: Python, SQL • 𝐃𝐚𝐭𝐚 𝐋𝐚𝐤𝐞 𝐃𝐞𝐬𝐢𝐠𝐧: Centralized data integration • 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: Workflow automation, Airflow DAGs • 𝐑𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠 & 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬: Data analysis, Business Intelligence 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: • Led the migration of data from Redshift to Snowflake, optimizing the data warehouse for better scalability. • Refactored legacy code and integrated Airflow for more efficient orchestration of ETL jobs. • Managed AWS services (MWAA, Redshift, S3, ECS, EKS) to improve data processing and reduce costs. • Automated and streamlined data pipelines with Airflow, saving time and resources on manual tasks. • Designed a centralized data lake, enabling seamless integration of various data sources across the business. • Worked with the analytics team to improve reporting systems and ensure data was accessible for reporting. • Implemented data validation scripts, ensuring the integrity and accuracy of business-critical data.

Data Engineer at Meta, Sep 2020 - Oct 2021 · 1 yr 2 mos, Chicago, Illinois, United States, 𝐒𝐮𝐦𝐦𝐚𝐫𝐲: At Meta, I worked on enhancing marketing analytics by designing and building ETL processes to handle brand tracker data and KPIs. I automated reporting systems, developed data validation scripts, and created dashboards that provided critical insights for ad campaigns, marketing spend, and brand performance. 𝐒𝐤𝐢𝐥𝐥𝐬: • 𝐄𝐓𝐋 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Spark, APIs, ETL Jobs • 𝐂𝐥𝐨𝐮𝐝 𝐓𝐨𝐨𝐥𝐬: AWS • 𝐃𝐚𝐭𝐚 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Tableau, Data Studio • 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: Python, SQL • 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: Data validation scripts • 𝐑𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠 & 𝐌𝐞𝐭𝐫𝐢𝐜𝐬: KPI development, Marketing Analytics 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: • Led the creation of KPIs for brand tracker metrics, providing actionable insights into multiple Facebook products. • Converted business requirements into technical specifications for building data pipelines and dashboards. • Built Spark-based ETL jobs to extract and transform data from multiple ad campaign sources. • Developed automated data validation scripts that improved data integrity and reduced manual errors by 20%. • Designed and developed dashboards to track key business metrics (Spend vs. Sales, Social Media Performance). • Enhanced cross-functional data workflows, ensuring accurate and timely reporting for multiple marketing teams. • Streamlined the process of marketing analytics, providing better and faster insights for decision-making.

Data Science Engineer at Blue Yonder, Jan 2019 - Aug 2020 · 1 yr 8 mos, Tampa, Florida, United States, 𝐒𝐮𝐦𝐦𝐚𝐫𝐲: In my role as Data Science Engineer at Blue Yonder, I designed and implemented data pipelines using AWS Glue, managed ETL workflows with Apache Airflow, and contributed to demand forecasting models that directly supported business decision-making. I also worked closely with data science teams to ensure the integration of various data sources for real-time analysis. 𝐒𝐤𝐢𝐥𝐥𝐬: • 𝐄𝐓𝐋: AWS Glue, Apache Airflow • 𝐂𝐥𝐨𝐮𝐝 𝐓𝐨𝐨𝐥𝐬: AWS • 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Demand forecasting, AWS SageMaker • 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: Python, SQL • 𝐃𝐚𝐭𝐚 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧: Centralized data system • 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: Workflow automation, DAGs 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: • Built AWS Glue-based data pipelines to streamline data extraction, transformation, and storage in AWS S3. • Implemented Apache Airflow DAGs for automating ETL processes, improving system reliability. • Developed demand forecasting models using AWS SageMaker, significantly improving business decision-making. • Created SQL queries to prepare data for analytics dashboards and machine learning models. • Worked closely with data scientists to integrate various data sources into centralized analytics systems. • Automated manual data processing tasks, improving efficiency and reducing errors. • Collaborated with stakeholders to ensure data solutions aligned with business objectives.

Research Associate at University of South Florida, Aug 2017 - Dec 2018 · 1 y 4 mo, Tampa

Senior Data Analyst at Accenture India, Aug 2013 - Jul 2017 · 3 y 11 mo, Mumbai

Education

Master of Science - MS, Business Analytics and Information System, University of South Florida

Bachelor of Technology (BTech), Electrical, Electronics and Communications Engineering, Guru Ghasidas University

Public links

github: https://github.com/sjsingh91