Akanksha Singh

Client: ABN AMRO, The Netherlands

• Built and maintained scalable, efficient ETL pipelines using Azure Data Factory, Azure Databricks, and SQL for structured and unstructured data.
• Developed data transformations, business logic, and data models in collaboration with cross-functional teams and business stakeholders.
• Designed monitoring frameworks using Azure Monitor to ensure pipeline reliability and data integrity.
• Ensured pipeline performance, scalability, and data quality through continuous optimization.
• Mentored junior team members on tools, best practices, and data engineering workflows.
• Created and maintained technical documentation and contributed to process improvements for better data operations and team efficiency.
• Tech Stack: Azure (ADLS, Data Factory, Databricks, Monitoring), PySpark, ETL, SQL

• Led multiple end-to-end data projects, from requirement gathering and architecture design to development, monitoring, testing, and user training.
• Designed and implemented a reusable ETL framework to ingest data from different sources, supporting the dunning process for automated collections and follow-ups.
• Developed and scheduled AWS Glue jobs to perform data transformations and implement business logic.
• Migrated existing legacy data warehouses to Snowflake, improving performance and scalability.
• Automated daily ingestion of input files from S3 to Snowflake using Snowpipe, applied transformation logic, and delivered reports in CSV format back to S3.
• Successfully delivered POCs and stakeholder demos to showcase data engineering solutions and validate business value.
• Created AWS Lambda functions to trigger and move data from S3 to Amazon Aurora.
• Led and mentored a team of 4 engineers to design and develop scalable, business-focused solutions.
• Tech Stack: PySpark, Snowflake, AWS (Glue, Lambda, S3, athena, aurora), JIRA, Git

• Developed Python automation scripts to validate web application functionality pre- and post-migration, reducing manual data analysis effort by 75%
• Proficient in Python, with hands-on experience across all phases of the SDLC and working knowledge of Agile development practices
• Analyzed and validated datasets using SQL for reporting and quality checks
• Tech Stack: Python, AWS, SQL