Devarasetty Anand — Data Engineer

I’m a Data Engineer & Analytics Professional with 6+ years of experience building scalable, reliable data platforms across EdTech, Retail, E-commerce, and Omnichannel businesses. My journey from analytics → ELT engineering → cloud data platforms has shaped me into a well-rounded engineer who doesn’t just move data—but turns raw data into trusted, business-ready intelligence. Across organizations like Rizee, Wonderchef, Tutorialspoint, and Kroger, I’ve worked on high-impact problems such as: 1. Integrating multi-channel data into a single source of truth 2. Designing ELT pipelines that scale with enterprise workloads 3. Building analytics-ready models for daily business decisions 4. Improving data quality, reliability, and performance 5. Automating reporting, insights, and operational workflows I’ve supported systems handling millions of learning events, thousands of SKUs, multi-terabyte datasets, and complex retail supply-chain processes. 🔧 What I Do Best 1. Snowflake Data Engineering ELT pipelines, Snowpipe, Streams & Tasks Query & warehouse optimization, cost governance 2. Cloud & ETL Engineering AWS S3, Glue, Python automation CI/CD for data pipelines 3. Data Modeling & Analytics Engineering Fact & dimension models Domain-driven design, curated marts dbt models, tests, documentation, macros 4. Advanced SQL & Business Analytics Sales, supply chain, funnels, retention Marketing ROI & learning analytics KPI frameworks & executive dashboards I bridge engineering, analytics, and business, ensuring data is not just collected—but trusted, accessible, and actionable. 📊 My Impact 🚀 Reduced manual reporting by 40–50% through scalable pipelines 💰 Improved model runtime & warehouse cost by 25–35% 🧩 Built unified data layers across web, app, CRM, marketplaces & retail outlets 📈 Enabled leadership insights across sales, promotions, inventory, student performance, and marketing ROI ✅ Strengthened data quality using automated validation & monitoring frameworks Quality, performance, and outcomes matter to me—not just building pipelines. 🎯 Current Mission To contribute to world-class data platforms in product-based companies and grow into a Senior / Lead Data Engineer, driving architecture, performance, and scalable analytics systems. 🤝 Let’s Connect If you’re working on data platforms, solving analytics challenges, or exploring Snowflake & cloud data engineering, I’d love to connect and exchange ideas.

Stackforce AI infers this person is a Data Engineer specializing in scalable data platforms for EdTech and Retail industries.

Location: Hyderabad, Telangana, India

Experience: 5 yrs 8 mos

Skills

Snowflake Data Engineering
Cloud & Etl Engineering
Data Quality Frameworks
Data Modeling & Analytics Engineering

Career Highlights

Reduced manual reporting by 40-50% through automation
Improved model runtime and warehouse cost by 25-35%
Built unified data layers across multiple platforms

Work Experience

AshuDividend Software Solutions Pvt Ltd

Snowflake Data Engineer (1 yr 10 mos)

Tutorialspoint

Sr Marketing Analytics (5 mos)

Healux International

Analytics Engineer (1 yr 1 mo)

swiss mobi

Associate Analyst (2 yrs 4 mos)

Education

2019 at Guru Nanak Institutions(GNI)

Devarasetty Anand

Data Engineer

Hyderabad, Telangana, India5 yrs 8 mos experience

Key Highlights

Reduced manual reporting by 40-50% through automation
Improved model runtime and warehouse cost by 25-35%
Built unified data layers across multiple platforms

Stackforce AI infers this person is a Data Engineer specializing in scalable data platforms for EdTech and Retail industries.

Contact

Skills

Core Skills

Snowflake Data EngineeringCloud & Etl EngineeringData Quality FrameworksData Modeling & Analytics Engineering

Other Skills

SnowflakeSQLdbtAWS S3SnowpipeStreams & TasksPythonTableauData ModelingELT PipelinesAgile/ScrumAWS GlueS3ETL/ELT PipelinesWorkflow Automation

About

Experience

Ashudividend software solutions pvt ltd

Snowflake Data Engineer

Mar 2024 – Jan 2026 · 1 yr 10 mos · Hyderabad · Remote

🔹 Role Summary
Worked as a Snowflake Data Engineer for Retail Analytics & Supply Chain teams, building scalable ELT pipelines, integrating large enterprise datasets, and enabling analytics for sales, inventory, promotions, and store operations. Delivered reliable Snowflake models and automated workflows that improved reporting accuracy, performance, and decision-making across the organization.
🔹 Key Responsibilities & Achievements
Built end-to-end Snowpipe + COPY ingestion pipelines to automate loading of POS sales, product, and inventory data from AWS S3 into Snowflake.
Developed optimized ELT models (raw → stage → core → marts) using SQL/dbt, improving model runtime by 30–40%.
Implemented Streams & Tasks to support incremental and near–real-time updates for sales, promotions, and stock movements.
Designed scalable dimension and fact models for sales, product, store, customer, and promotion analytics.
Optimized queries using micro-partitioning, pruning, clustering, and caching, reducing warehouse costs by 25–35%.
Created dbt tests, documentation, macros, and CI/CD workflows to ensure reliable deployments across environments.
Built automated data validation and anomaly checks, improving data quality for downstream BI teams.
Supported Tableau/Power BI teams by delivering clean marts for sales KPIs, store performance, category insights, and forecasting analytics.
Automated reporting using Snowflake Tasks and scheduling frameworks, reducing manual effort by 40%.
Collaborated across TechM, Kroger, and vendor teams to manage schema changes, optimize pipelines, and ensure smooth production releases.
🔹 Tools & Technologies
Snowflake, SQL, dbt, AWS S3, Snowpipe, Streams & Tasks, Python, Tableau, Git,Data Modeling, ELT Pipelines, Data Quality Frameworks, Agile/Scrum.

SnowflakeSQLdbtAWS S3SnowpipeStreams & Tasks+8

Tutorialspoint

Sr Marketing Analytics

Sep 2023 – Feb 2024 · 5 mos · Hyderabad · On-site

🔹 Role Summary
Acted as a core data engineer within the Marketing Analytics team, building scalable data pipelines, integrating multiple data sources, and enabling performance analytics for millions of learners across Tutorialspoint’s online learning ecosystem. Streamlined data flows from web, app, CRM, and marketing platforms to Snowflake, enabling accurate reporting, user behavior insights, and data-driven marketing strategies.
🔹 Key Responsibilities & Achievements
Designed and orchestrated ETL pipelines using AWS Glue + Python, automating ingestion of user activity logs, course engagement metrics, marketing data, and subscription events into Snowflake.
Built optimized Snowflake data models for user journeys, content consumption, campaign analytics, and subscription funnels, improving query performance by 35–40%.
Developed unified data layers consolidating data from web events, app analytics, LMS modules, CRM, and Google Analytics, reducing data silos and improving cross-team visibility.
Implemented advanced SQL transformations for session tracking, student retention curves, test performance, and course effectiveness, contributing to more accurate business KPIs.
Built reusable Python scripts for data validation, schema checks, anomaly detection, improving data trust for marketing and product stakeholders by 25%.
Conducted deep analyses on learning patterns, video engagement, topic-level consumption, assessment performance, offering insights that improved content strategy and course recommendations.
Streamlined monthly reporting workflows by automating Snowflake tasks and Glue jobs, reducing manual effort by 40%.
Documented end-to-end data engineering processes, pipeline logic, and metric definitions to ensure team-wide clarity and efficient onboarding.
🔹 Tools & Technologies
SQL, Snowflake, AWS Glue, Python, Tableau, S3, ETL/ELT Pipelines, Data Modeling, Workflow Automation, Data Quality Checks, Agile Methodology

SQLSnowflakeAWS GluePythonTableauS3+7

Healux international

Analytics Engineer

Jul 2022 – Aug 2023 · 1 yr 1 mo · Bengaluru · Hybrid

🔹 Role Summary
Worked as an Analytics Engineer supporting omnichannel retail and D2C business. Built and optimized data models, automated sales & inventory pipelines, and delivered insights across product, supply chain, and marketing teams. Company’s online channels to improve forecasting, stock planning, and revenue performance.
🔹 Key Responsibilities & Achievements
Designed and maintained scalable data models for retail sales, SKU performance, marketing spend, and inventory movement using SQL and Python.
Automated daily and weekly reporting pipelines, reducing manual reporting time by 40–50% across sales, operations, and finance teams.
Consolidated data from offline stores, marketplaces (Amazon, Flipkart), brand website, and distributor networks, improving cross-channel visibility and reducing mismatches by 25%.
Conducted advanced analytics on SKU-level performance, store-wise productivity, stockouts, returns, and pricing, enabling better decision-making for category and supply chain teams.
Built dashboards in Tableau to track revenue trends, contribution margins, slow/fast-moving items, and demand across regions.
Collaborated with marketing and digital teams to analyze campaign ROI, attribution, CAC, retention, and repeat purchase patterns for D2C channels.
Implemented data validation checks and QA processes, improving data reliability for leadership reports and monthly business reviews (MBRs).
Provided insights to optimize inventory allocation and reduce overstock situations by ~10% through better forecasting inputs.
Documented end-to-end data workflows, transformation logic, and metric definitions to ensure consistency and smooth stakeholder understanding.
🔹 Tools & Technologies
SQL, Python, ETL Concepts, Excel, Tableau, Power BI, Google Analytics, Data Modeling, Data Quality Checks, Agile Methodology

SQLPythonETL ConceptsExcelTableauPower BI+5

Swiss mobi

Associate Analyst

Feb 2020 – Jun 2022 · 2 yrs 4 mos · Hyderabad · Remote

🔹 Role Summary
Supported large-scale edu-tech analytics operations by working with high-volume student performance data, course engagement metrics, and test-preparation insights. Automated learning performance reports, improved data accuracy checks, and delivered insights that enhanced product decisions for student learning journeys and exam preparation outcomes.
🔹 Key Responsibilities & Achievements
Analyzed large datasets related to student performance, test attempts, question-level analytics, and course engagement using SQL, Python, and Excel, improving analytical accuracy by 12–15%.
Automated daily and weekly dashboards in Tableau/Power BI to track user activity, course progress, test scores, and retention, reducing manual reporting effort by 30–40%.
Executed data validation and quality checks across learning modules and practice tests, reducing metric discrepancies by 20%.
Collaborated with product, academic, and marketing teams to provide insights on student dropout patterns, engagement funnels, session duration, and learning outcomes.
Performed deep-dive analysis on mock test performance, subject-wise accuracy, question difficulty distribution, and student learning curves, helping improve overall user retention by ~5%.
Developed reusable SQL scripts for repetitive business queries such as daily active users (DAU), test participation rate, and completion trends.
Assisted in troubleshooting data mismatches and reporting inconsistencies by validating event tracking, assessment data, and content consumption logs.
Documented analysis workflows, data definitions (course, module, question-level metrics), and reporting logic to maintain clarity and support cross-team collaboration.
🔹 Tools & Technologies
SQL, Python, Excel, Tableau, Power BI, JIRA, Confluence, Agile Methodology, Data Quality Checks, ETL Concepts