Neeraja Chekka

Project: Revenue Leakage Identification – Spark Audit Interface (SAI)

Technologies: Azure (ADF, Power Automate, ADO, BLOB, Power BI), Databricks (Python), Snowflake

Overview:
Designed and deployed a Spark-based audit interface to streamline revenue assurance processes and identify potential revenue leakages across multiple business streams.

Key Contributions:

• Architected a unified Spark-based audit framework, serving as a single source of truth for revenue validation.
• Developed automated data validation processes to detect anomalies and revenue discrepancies across business streams such as WAN and LFC.
• Implemented fuzzy matching algorithms for enhanced data accuracy and validation.
• Built ETL pipelines to seamlessly ingest and transform data from diverse source systems.

Key Achievements:

• Delivered an end-to-end automation solution for contract extraction and leakage identification.
• Enabled proactive revenue monitoring and recovery through automated workflows for credit adjustments (overbilling) and revenue recovery (underbilling).
• Prevented revenue leakages worth over NZD 1M by streamlining auditing processes.

Project: DataGPT – AI-Powered Analytics Assistant

Technologies: Azure (ADF, ADO, BLOB, Power BI), Snowflake

Overview:
Developed DataGPT, an AI-powered analytics assistant designed to simplify and automate data analysis through natural language queries, enabling business users to extract actionable insights seamlessly.

Key Contributions:

• Integrated diverse data sources and developed API connections for streamlined data access.
• Designed and implemented a robust response delivery system for efficient query handling.
• Automated end-to-end data processing pipelines for data extraction and transformation, ensuring real-time insights.

Key Achievements:

• Simplified complex data workflows, enabling business stakeholders to make data-driven decisions effectively.
• Enhanced business intelligence through real-time availability of insights, driving improved operational efficiency.
• Ensured data quality through rigorous testing, validation, and monitoring of all data assets, minimizing inaccuracies and inconsistencies.
• Reengineered existing ETL workflows to improve performance by identifying bottlenecks and optimizing code accordingly.
• Championed the adoption of agile methodologies within the team, resulting in faster delivery times and increased collaboration among team members.

Project: Multicloud Management Services (MCMS – R&D)

Technologies: Cloudera Data Platform, Ansible Playbook, Hadoop, Spark, Python, Ranger, AWS, Acceldata

Overview:
Developed scalable and automated solutions for managing hybrid and multicloud infrastructures across AWS, Azure, GCP, and Alibaba Cloud. Enhanced operational efficiency through advanced monitoring, reporting, and service optimization.

Key Contributions:

• Built and optimized data pipelines and profiling tools using Spark and Pandas.
• Automated infrastructure management with Ansible Playbook for seamless configuration.
• Leveraged Cloudera Data Platform and Hadoop for large-scale data processing.
• Integrated Acceldata for data quality monitoring and performance enhancement.

Key Achievements:

• Delivered a standardized multicloud management framework supporting SMB and enterprise clients.
• Improved system reliability and operational efficiency using SRE principles.
• Enabled businesses to seamlessly transition to and operate in hybrid cloud environments.

Project: Talend to NiFi Migration
Duration: Oct 2018 – Dec 2019
Technologies: TIS (Talend Enterprise), TOS (Talend Open Studio), Apache NiFi

Overview:
Migrated Talend-based ETL frameworks to Apache NiFi, optimizing performance and ensuring system stability.

Key Contributions:

• Analyzed the existing Talend framework to map functionalities for NiFi.
• Converted Talend logic into NiFi workflows using equivalent native functions.
• Conducted performance and regression testing to ensure seamless platform migration.
• Stabilized the platform for enhanced operational reliability.

Project: Greenplum to Hortonworks Migration
Duration: Sep 2017 – Oct 2018
Technologies: Hive, Spark SQL, PySpark, Python, Talend

Overview:
Executed a seamless migration of Greenplum database workflows to Hortonworks, leveraging Spark and Hive for efficient data processing.

Key Contributions:

• Migrated Greenplum artifacts, including mirror tables and consumption layers, to Hortonworks.
• Translated Greenplum (pgsql) logic into Spark and Hive workflows.
• Developed and scheduled Spark jobs in Talend to streamline data workflows.
• Optimized code for improved system performance and scalability.

Project: GE Transportation Datalake
Duration: Dec 2016 – Aug 2017
Technologies: Greenplum, Talend

Overview:
Designed and implemented ETL solutions for GE Transportation’s Datalake, ensuring robust and automated data management.

Key Contributions:

• Built Talend workflows for loading data into Greenplum for visualization teams.
• Designed an automation framework to dynamically handle schema changes, resolving recurring production issues.
• Engaged with end-users to gather and fulfill data requirements.
• Played a key role in data discovery, onboarding critical datasets for business needs.

Project: ARR – Asia Regulatory Reporting (APAC)

Role: Talend and Java Developer
Technologies: Talend (ETL), UNIX, Oracle PL/SQL, Java/J2EE, Spring, Adobe Flex

Overview:
Developed a robust reporting system to meet compliance requirements for financial institutions in the APAC region, delivering automated trade and valuation reports for regulatory bodies such as FSC and GTSM.

Key Contributions:

• Designed and implemented Talend ETL pipelines for automated data processing and reporting.
• Migrated Talend workflows from Windows to UNIX environments using shell scripts.
• Created a user interface for critical data maintenance, enhancing reporting accuracy.
• Led data quality initiatives to ensure accurate and valid reporting.
• Conducted release planning and deployed DDL and Talend code in UAT and production environments.

Project: Daymon Interactions BI

Role: Talend Developer and Team Lead
Technologies: Talend (ETL), SQL, Redshift, Java, Tableau, AWS

Overview:
Implemented data integration and automation solutions to optimize retail service operations for Daymon Worldwide, enabling real-time insights and improved brand loyalty through data-driven marketing.

Key Contributions:

• Developed and executed ETL pipelines in Talend, transforming source data into Redshift target schemas.
• Automated data transfer and processing using AWS services such as S3 and ECS.
• Enhanced system performance through SQL optimization and process redesign.
• Integrated Tableau for business intelligence reporting, enabling actionable insights.
• Conducted rigorous testing to ensure high-quality data delivery and reliability.

Project: Data Ingestion Framework

Role: Talend and Hadoop Developer
Technologies: Talend (Big Data), MySQL, Hadoop, HDFS, Hive

Overview:
Developed a data ingestion framework to extract, transform, and load data from diverse relational systems into Hadoop, enabling scalable data processing for business analytics.

Key Contributions:

• Built ETL pipelines using Talend to automate data ingestion into HDFS and Hive tables.
• Designed incremental and full-load processes for efficient data refreshes based on user flags.
• Prepared low-level design documents and implemented optimized mappings.
• Conducted code reviews, unit testing, and deployment activities to ensure production readiness.
• Streamlined release processes, ensuring timely delivery of solutions.