CHAITANYA CHINTHOJU

Environment: AWS, Glue, S3, Python, Spark, Kinesis, Redshift, Athena, CloudWatch, GitHub, Bitbucket, CloudBees CI, and Excel Scripts.

• Designed AWS Glue ETL pipelines using Python to automate data ingestion, cleansing, validation, and curation for enterprise analytics.
• Built distributed Spark jobs to speed up transformations, improving processing scalability for large datasets.
• Implemented Redshift-based data warehouse models, optimizing performance for analytical and reporting workloads.
• Automated CI/CD using CloudBees CI and integrated SonarQube for code quality tracking, reducing release cycles by 40%.
• Developed multiple POCs for real-time ingestion using AWS Kinesis, enabling high-volume event streaming.
• Built Excel Office Scripts to automate reporting workflows, reducing manual effort by 95%, and improving accuracy.

Project 2 – Azure Cloud Modernization.

Environment: Azure Data Factory, Synapse, Blob Storage, Salesforce, Databricks, Redshift, S3, Airflow, Jenkins, SQL, PySpark, Power BI.

• Designed high-performance ETL pipelines in ADF and Databricks, improving throughput by 35% across massive datasets.
• Modernized the legacy warehouse to Synapse and Redshift, reducing reporting delays by 40%.
• Integrated SalesForce, Blob Storage, and AWS datasets for unified BI reporting, used by 100+ executives.
• Implemented Airflow and Jenkins workflows, enforcing data quality, lineage, and governance.

Project 1 – AWS Data Engineering

Environment: S3, Redshift, Glue, Lambda, Step Functions, DynamoDB, CloudWatch, Snowflake, Hive, PySpark, Python.

• Built scalable Glue and PySpark ETL pipelines, transforming ORC, Parquet, CSV, and text formats.
• Implemented serverless data orchestration using Lambda and Step Functions, reducing operations overhead by 44%.
• Designed event-driven microservices connecting S3, DynamoDB, and monitoring systems.
• Migrated curated datasets to Snowflake for downstream analytics.

Environment: S3, Redshift, Snowflake, Spark, Hive, Databricks, EC2, SQL, Python.

• Partnered with business teams to build analytical datasets for marketing and customer portfolio analysis.
• Automated Python and SQL data preparation for dashboards, reducing turnaround by 28%.
• Analyzed credit, loan, and repayment trends to drive targeted sales initiatives.

Environment: Oracle, Teradata, SQL Developer, Jenkins, and GitHub.

• Developed complex SQL queries, procedures, and views across Oracle and Teradata, improving performance significantly.
• Built ETL data structures, and ensured quality through cleansing and validation logic.
• Optimized database performance by implementing indexing strategies and query tuning techniques.

• Led full-cycle technical recruitment across IT, non-IT, and campus hiring, partnering with leadership to fulfill niche skill requirements and streamline hiring operations, and managed vendor coordination, candidate sourcing, screening, interviews, and offer negotiations, ensuring high-quality hiring pipelines.
• Directed hiring analytics, recruitment reporting, and workforce planning, improving hiring efficiency, and reducing no-show ratios through strategic process enhancements.
• Supported HR generalist functions, including onboarding, training, employee engagement, and campus program management, strengthening organizational culture and operational workflows.

• Recruited for advanced product engineering skills across C/C++, Java, Linux/Android, mobility, multimedia, and device technologies.
• Handled sourcing, screening, interview coordination, negotiations, and candidate management for engineering teams.

• Executed the full hiring lifecycle for Microsoft, Java, Data Warehousing, and enterprise stack roles.
• Facilitated onboarding sessions, ensuring compliance with company policies and procedures.

• Delivered end-to-end hiring for IBM and Accenture across contract and permanent staffing models.
• Successfully placed candidates in various IT roles, including software developers, network engineers, data analysts, and project managers.