Data Engineer with 6+ Years in Cloud ETL and Analytics

PremChand Are

Data Engineer

472-***-**** **************@*****.*** Linkedin

PROFESSIONAL SUMMARY

Results-driven Data Engineer with 6 years of experience designing, developing, and optimizing scalable data pipelines and analytics platforms across AWS, Azure, and GCP environments. Skilled in building robust ETL workflows, data models, and cloud data warehouses using tools like Airflow, dbt, Spark, Databricks, and Snowflake. Strong background in SQL, Python, and data modeling with expertise in automating data workflows, improving performance, and enabling data-driven decision-making. Adept at collaborating with cross-functional teams to deliver clean, reliable, and high-impact data solutions that support business intelligence, analytics, and machine learning initiatives. TECHNICAL SKILLS

• Programming & Analysis: SQL (T-SQL, PL/SQL, PostgreSQL, SQL Server, Oracle), Python (Pandas, NumPy, PySpark, Matplotlib, Seaborn)

• Databases: PostgreSQL, Oracle, MongoDB, DynamoDB, SQL Server

• ETL & Data Pipelines: SSIS, Alteryx, Talend, AWS Glue, Apache Airflow, dbt (Data Build Tool)

• Cloud & Big Data Platforms: AWS (S3, Redshift, Glue, Athena, Lambda), Azure (Data Factory, Data Lake), GCP

(BigQuery), Databricks, Spark (PySpark, Spark SQL), Kafka, Hive

• Data Modeling & Warehousing: Star Schema, Snowflake Schema, Kimball Methodology, Data Vault, Erwin Data Modeler, Snowflake, Redshift

• Visualization & BI Tools: Tableau, Power BI, Looker

• Statistical & Predictive Analytics: A/B Testing, Regression, Time Series Analysis, Forecasting, Machine Learning (Scikit- learn)

• Version Control & DevOps: Git, GitHub, Jenkins, Docker, Terraform PROFESSIONAL EXPERIENCE

Senior Data Engineer Petco Sep 2025 – Present

• Designed and developed end-to-end ETL pipelines using SQL Server Integration Services (SSIS) and Python, automating data flow across multiple sources.

• Created and optimized complex SQL queries, stored procedures, and views, improving data extraction speed by 30%.

• Designed and implemented end-to-end ETL pipelines using SSIS and Python, streamlining data ingestion from multiple retail, e-commerce, and inventory systems.

• Optimized complex SQL queries, stored procedures, and views, improving data extraction performance by 30% and accelerating analytics for merchandising and finance teams.

• Migrated legacy on-premises data to AWS Redshift, cutting storage costs and enhancing scalability for large-scale transactional data.

• Developed robust data validation and quality frameworks in Python (Pandas) to ensure high accuracy in sales and customer datasets.

• Built data models following Kimball methodology (Star Schema) to support retail analytics, inventory tracking, and demand forecasting.

• Integrated external data sources (APIs, CSV, Excel) through Talend and Alteryx, improving operational data completeness.

• Delivered interactive dashboards in Tableau and Power BI, enabling leadership to monitor product performance and store KPIs.

• Scheduled and monitored daily ETL workflows using Apache Airflow, ensuring timely data availability across analytical platforms.

• Collaborated with marketing, operations, and finance teams to define data governance and metadata standards.

• Documented architecture and data flow processes to streamline knowledge transfer and onboarding for new engineers. Senior Data Engineer TD Bank Aug 2024 – Aug 2025

• Architected and managed scalable data pipelines using AWS Glue, Apache Airflow, and dbt, automating ingestion from 20+ banking data sources.

• Designed and deployed a Snowflake data warehouse to centralize risk, compliance, and customer analytics.

• Developed efficient data transformation scripts using PySpark, enabling high-volume batch data processing.

• Optimized Spark job performance, reducing ETL runtime by 40% through tuning partitioning and caching strategies.

• Implemented CI/CD pipelines for ETL processes using GitHub Actions and Jenkins, ensuring reliable production deployments.

• Led the migration of analytics workloads from Redshift to Snowflake, improving performance by 50% and reducing maintenance overhead.

• Partnered with data scientists to produce machine learning pipelines for fraud detection and customer segmentation.

• Strengthened data lineage and quality monitoring using dbt tests and Airflow sensors.

• Administered data access controls through AWS IAM and Snowflake roles, aligning with financial compliance standards.

• Provided mentorship to junior engineers on data modeling, version control, and orchestration best practices. Data Engineer TCS Aug 2019 – Dec 2022

• Designed and maintained ETL processes to consolidate customer, inventory, and sales data into an AWS Redshift and S3-based data warehouse, enabling enterprise-level reporting and analysis.

• Developed and maintained real-time data streaming pipelines using Kafka and Spark Structured Streaming, processing 10M+ events per day across multiple client systems.

• Designed data lake architecture on AWS (S3, Glue Catalog, Athena) to unify structured and semi-structured client data sources.

• Built and managed Airflow DAGs for ETL orchestration, ensuring SLA compliance for global business operations.

• Automated infrastructure provisioning with Terraform and containerized ETL workloads using Docker, enabling reproducible deployments.

• Engineered distributed data transformation pipelines in Databricks leveraging PySpark for large-scale processing.

• Delivered Snowflake-based data warehouse solutions for analytics teams, enabling self-service reporting for 100+ users.

• Partnered with BI developers to deliver Tableau and Looker dashboards, improving client KPI visibility and data-driven decision- making.

• Conducted root cause analysis and data reconciliation to ensure consistency and accuracy across data environments.

• Implemented data versioning, source control, and CI/CD integration with Git and dbt.

• Advocated best practices in data governance, pipeline optimization, and performance tuning across project teams. EDUCATION

Northwest Missouri State University May 2024

Master of Science in Applied Computer Science

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