Anubha Gupta

• Enhanced overall team productivity with continuous training and mentoring of junior engineers. Transitioned a team of 3 mid-level professionals to a team 2 senior and 2 mid-level professional by individuals' growth & hiring.
• Improved engineering processes by streamlining workflows and implementing efficient project management techniques.
• Identified areas of improvement in existing systems, providing recommendations that resulted in significant cost savings over time. Achieving 40% reduction in resources consumed to process the same amount of data
• Implemented data quality score & control measures to quantify & reduce errors, resulting in increased customer satisfaction.

• Working on datalake requirements including ingestion, curation and data quality needs. Managing the data for 36 countries globally.
• Writing, maintaining, optimizing ETL pipelines.
• Stack Used : Airflow, Terraform, Dataproc , Spark, SQL, Bigquery, Python
• Ensured data quality through rigorous testing, validation, and monitoring of all data assets, minimizing inaccuracies and inconsistencies.

Analytics Data Warehouse & BI , Grab , Singapore

Senior Data Engineer ( Mar 2021 - Sep 2022 )

• Design and Migration of Central DW, consuming processing and refining data for multiple products in various formats, including data from products, rewards, performance and brand health (Survey, NPS etc.), working with various data consumers and streamlining their asks, helping them with their data requirements
• A key member for BI team involved in public disclosures, IPO & investor reporting, curating and defining metrics and deriving business insights from the data and building narratives
• Worked on org-wide reconciliation tool, to ensure quality of migration and seamless UAT endorsement

Stack Used : Azure Cloud Stack, Python, Databricks

Data Platform Evolution

• Building a unified data platform to serve as a single source which serves as source to various marketing, sales and government projects
• Developing a generic anonymization framework for all incoming data sources to ensure PDPA compliance for all PII fields. This achieved a manual effort reduction of 15 man-weeks bi-annually.
• Implement an interface layer with a 360 metrics for various telco dimensions for business data mining and data scientists
• Hybrid Architecture implementation using a custom LB between AWS cloud and on-premise cluster

Finance and Risk Data Mart ( Aug 2017 - Mar 2020 )

• Build a data layer to serve various risk and finance analysis applications and engines.
• Worked on developing generic Metadata-driven framework to process source data based on user provided conditions.
• Developed Rejection logic to enforce primary key constraint on Hive Tables.
• Forward Dated Data Enrichment process which allows the users to add/ update and delete the data in the dataset allowing for manual adjustment
• Implemented automated batch monitoring using spark & java to monitor the daily data for frontend platform.
• any quality breaches or any upstream issues and amend and alert automated emails.

Automated Communication Surveillance System ( Oct 2016- Aug 2017 )

• To analyse the data from various communication channels and present on a common frontend platform.

• Developed a generic code for processing of zip files and xml files and converting the same into a structured data format for lexicon analysis, business rule validation and tagging, alerting and representation.

• Migration of the data available in legacy systems to big data systems to be consumed by SAS applications. This project helped save a 20k SGD per year for the organization.
• Custom data migration tool which can be configured to migrate data as per requirement i.e Daily, monthly, historical & full.
• Implemented a generic feature to translate RDBMS schema to AVRO schema
• Worked on implementing a reconciliation and data quality tool check for the migrated data sets