Akhil Shrivas

Associate Data Engineer

Cloud Nexus DigiWeb Services Pvt. Ltd.

Sep 2025 - Jul 2026

Developed Python-based data engineering, backend, and automation workflows for data processing, API integration, ETL, and cloud-based applications. Used Pandas, NumPy, PySpark, and Dask for data transformation, cleaning, validation, analysis, and efficient processing of structured and large-scale datasets. Built and maintained ETL/ELT pipelines using Python, SQL, Apache Airflow, dbt, and cloud services for automated and reliable data processing. Designed database schemas, optimized SQL queries, and developed data-access workflows across PostgreSQL, MySQL, SQL Server, MongoDB, and other data platforms. Worked with relational and NoSQL databases including PostgreSQL, MySQL, SQL Server, MongoDB, and Cassandra for application and data engineering workloads. Built and supported data warehouse workflows using Snowflake, Amazon Redshift, and Google BigQuery, including data ingestion, transformation, modeling, and validation. Used Apache Spark and PySpark for distributed data processing and transformation of large datasets, applying scalable processing techniques for data-intensive workloads. Worked with Hadoop and distributed data-processing concepts for handling large-scale datasets and understanding scalable data engineering architectures. Developed RESTful APIs using Python and FastAPI, implementing request/response models, validation, backend logic, and integrations with databases and third-party services. Developed reusable Python scripts for data extraction, transformation, automation, validation, file processing, and operational workflows. Worked with AWS services including S3, Glue, Lambda, EMR, API Gateway, IAM, and CloudWatch for cloud-based data and application workflows. Worked with Azure data services including Azure Data Factory, Azure Synapse Analytics, and ADLS for data integration, processing, and analytical workloads. Worked with GCP services including Dataflow and BigQuery for cloud-based data processing and analytical workloads. Implemented data quality checks, validation rules, logging, monitoring, and error handling to identify and troubleshoot data-processing failures. Debugged application and pipeline issues by analyzing logs, reproducing failures, tracing root causes, and implementing corrective solutions. Optimized data-processing workflows, SQL queries, schemas, and pipeline execution to improve reliability and processing efficiency. Used Apache Airflow for workflow orchestration, scheduling, dependency management, monitoring, and automated execution of data pipelines. Used Git and GitHub for version control and collaborated with development and data teams through issue tracking, code changes, documentation, and Agile workflows. Created technical documentation and maintained project updates, troubleshooting procedures, reusable scripts, and data engineering workflows.