Anu P Email and Phone Number

• Analyse the requirements, defect logs, and come up with clarification logs to validate with customers.• Responsible for the execution of big data analytics, predictive analytics and machine learning initiatives.• Proficient in developing and managing data transformation workflows using DBT. • Experience in developing robust data pipelines using DBT and Snowflake to ensure reliable and accurate data flow.• Led the design and development of data engineering solutions, utilizing ontological frameworks such as BFO (Basic Formal Ontology) and CCO (Common Core Ontology) to standardize and enhance data management.• Developed Scala scripts, UDF are using both data frames/SQL and RDD in Spark for data aggregation, queries and writing back into S3 bucket.• Wrote, compiled, and executed programs as necessary using Apache Spark in Scala to perform ETL jobs with ingested data. • Developed, maintained, and optimized graph databases and triple stores, prioritizing data integrity, consistency, and performance.• Implemented and managed semantic web technologies, including RDF, OWL, SPARQL, and SHACL, to enable effective data interoperability and reasoning.• Worked on Big data on AWS cloud services i.e. EC2, S3, EMR and DynamoDB.• Implemented robust security measures for data stored in Redis, VectorDB, and CouchDB, including encryption, authentication, and access controls. Ensured compliance with data privacy regulations and organizational security policies.• Implemented End to End solution for hosting the web application on AWS cloud with integration to S3 buckets.• Used Spark Streaming to divide streaming data into batches as an input to Spark engine for batch processing.

• Implementing reusable codes which can be used through the project like Stored Procedures. • Developed file cleaners using Python libraries and made it clean. • Implemented error and failure handlings within using event handlers, check points, custom logs to monitor execution. • Created clone production data for code modifications and testing and to perform troubleshooting analysis for critical issues. • Created a Lambda deployment function and configured it to receive events from S3 buckets. • Define virtual warehouse sizing for different types of workloads to reduce the burden on warehouses. • Creating external stages in AWS S3 and placing the static data hive files and then loading the files intoSnowflake using file formats based on compressions and delimiters. • Worked for building cloud formation templates for SNS, SQS, LAMBDA, EC2, S3, IAM services implementation and integrated with service catalog. • Created DAGs to automate the process using python schedule jobs by Airflow. • Excellent SQL Developer skills including Stored Procedures, Indexed Views, User Defined Functions. • Used GitHub Pull request, Merge, Checkout to migrate Snowflake Parameterized CI/CD Scripts to promote higher environments. • Created external tables with various partitions using Hive, AWS Athena, Redshift. • Experience with event-driven and scheduled AWS lambda functions to trigger various AWS Resources. • Monitored the sizes of the tables in SF and applied clustering keys and deactivated automatic clustering. • Validating the downstream application reports (Bo) pointed to the Snowflake database. • Participated in weekly meetings, reviews, and user group meetings as well as communicating with stakeholders and business groups.

• Hands-on experience in writing complex SQL queries using Teradata SQL Assistance and T-SQL. • Strong experience in AWS data services, including AWS Glue, AWS Lambda, and Amazon S3. • Proficiency in SQL and data integration tools.Expertise in Snowflake data warehousing, including schema design, data modeling, and optimization techniques. • Knowledge of data governance, privacy regulations, and security best practices.Developed Automation Regressing Scripts for validation of ETL process between multiple databases like AWS, SQL Server using Python. • Developed Automation Regressing Scripts for validation of ETL process between multiple databases like AWS, SQL Server using Python. • Designed and developed data pipelines using Databricks Delta and Apache Spark to ingest, transform, andload large-scale data from various sources into a unified data lake for analysis and reporting purposes. • Implemented data quality checks and data validation routines in Databricks notebooks using Python, PySpark, and SQL for ensuring accuracy and completeness of data. • Created Complex SQL Queries using Views, Indexes, Triggers, Roles, Stored procedures, and User Defined Functions. • Ability to perform duties in a very fast-paced environment and ability to learn new technology.

• Created ETL packages where various control flow and data flow items are utilized to perform Transformations over OLTP data before loading into the data warehouse. • Designed and developed Packages to import and export data from MS Excel, SQL Server, and Flat files. • Debugged various packages using data viewers, break points and event handlers. • Designed ETL packages to deal with multiple data sources and load the data into target data sources by implementing multiple transformations using Talend. • Troubleshooting of issues by cross checking the jobs, Stored Procedures and Packages. • Generated on-demand and scheduled jobs for business analysis or management decisions using Talend Console. • Analyse root cause for certain jobs that failed to load and followed by a defect fixing procedure. • Understand and analyse new problems encountered in the monitoring. • Identify long running jobs and fix them. • Identified the missing source files for the day, by communicating with the source team and skip the flow accordingly. • Extensively worked with the production team for scheduling jobs and provided support from the onsite team towards holding/executing.