Data Engineer with 2+ years of experience in designing, building, and maintaining scalable data pipelines and data platforms. Strong expertise in ETL/ELT development using Snowflake, DBT, and Apache Airflow, with hands on experience in SQL, Python, and cloud services (AWS). Proven ability to optimize data workflows, ensure data quality, and support analytics through reliable and well-structured data infrastructure. Experienced in collaborating with analytics and business teams to deliver high-performance data solutions.
Data Engineer with 2+ years of experience in designing, building, and maintaining scalable data pipelines and data platforms. Strong expertise in ETL/ELT development using Snowflake, DBT, and Apache Airflow, with hands on experience in SQL, Python, and cloud services (AWS). Proven ability to optimize data workflows, ensure data quality, and support analytics through reliable and well-structured data infrastructure. Experienced in collaborating with analytics and business teams to deliver high-performance data solutions
Neeyamo is a leading technology-enabled global payroll and EOR solutions provider for multinational and micro-multinational corporations worldwide.
Grade: First class distinction.
Grade: First class distinction.
Below are the sample Data Analytics and Engineering projects
• Live stock data fetched from external API
• Real-time event streaming using Apache Kafka
• Data stored in S3-compatible storage (MinIO)
• Orchestrated workflow using Apache Airflow
• Cloud data warehousing in Snowflake
• Layered data modeling (Raw → Cleaned → Business Ready)
• Transformations managed using DBT
• Analytics delivered through Power BI
• Built an end-to-end ETL/ELT pipeline to ingest data from APIs and AWS S3 into
Snowflake.
• Developed DBT models with incremental loads and dimensional modeling for
analytics-ready datasets.
• Orchestrated pipelines using Apache Airflow with automated scheduling, retries, and
monitoring.
• Implemented data quality checks to ensure accuracy and reliability across datasets.
• Designed a scalable data ingestion pipeline using AWS Lambda to collect data from
external sources.
• Processed and transformed raw data into curated tables in Snowflake for reporting and
analytics.
• Automated workflows and failure handling using Apache Airflow.
• Optimized SQL queries and warehouse usage to improve performance and reduce costs
• Built a real-time data pipeline using AWS Lambda (Python) to fetch weather data from a Weather API and store it in Amazon DynamoDB.
• Leveraged DynamoDB Streams to automatically process and transfer data into Amazon S3.
• Integrated Snowflake (Snowpipe & External Stages) to load data from S3 for analytics.
• Automated hourly data ingestion using Amazon EventBridge, ensuring continuous and reliable data flow.
• Developed an interactive Power BI dashboard featuring a wide range of customized
visualizations, including bar, pie, donut, clustered bar, scatter plots, line, area
charts, maps, and slicers for data representation and analysis.
• Connected multiple data sources, joined tables, and implemented calculated fields
for data manipulation and enhanced visualizations.
• Delivered actionable insights through customized, visually engaging reports tailored
to business requirements.
• Analyzed customer shopping behavior using SQL and Python to identify trends, patterns,
and insights for a retail business.
• Conducted exploratory data analysis (EDA) to understand customer demographics, purchase
patterns, and product preferences. (discounts, reviews, seasonality, channels)
• Utilized clustering techniques to segment customers based on their shopping behavior and
provided actionable recommendations for targeted marketing strategies.
Below are the details to reach out to me!
Pune, India