Data Engineer Azure

Saisree Karineni

*******.********@*****.*** • 815-***-**** • LinkedIn

PROFESSIONAL SUMMARY:

Experienced Data Engineer and Analyst with around 6 years in building data pipelines, performing ETL processes, analyzing and translating complex technical requirements into effective solutions in Agile Environments. Proficient in advanced SQL querying, data mapping, modeling, and large-scale data migrations. Adept at leveraging Excel, data warehouse sourcing for comprehensive data analysis. Individual with strong problem-solving and analytical skills. EDUCATION:

Master of Science in Management Information Systems, Northern Illinois University, IL Aug 2022 Bachelor of Engineering in Computer Science, GITAM University, India May 2017 SKILLS:

Programming Languages/Big Data Tools: Python, Java, PySpark, Scala, R, SSIS, Spark, Hadoop, HDFS, MapReduce, Sqoop. Reporting/ Visualization Tools: Tableau, Power BI, QuickSight, Excel Databases: MySQL, SQL Server (T-SQL), Oracle (PL/SQL), Postgre SQL, Cosmos DB, Cassandra, dynamo DB, Mongo DB Azure Cloud Services: Azure Data Factory, Data Lake, ADLA, ADLS, BLOB, Databricks, SQL DB, Azure DevOps, HDInsight. AWS Cloud Services: EC2, S3, AWS Kinesis, Firehose, Redshift, EMR, RDS, Glue, Athena, ECS, SNS, Lambda. Data Warehousing/ETL/Tracking Tools: Snowflake, Azure Synapse Analytics, Apache Airflow, Apache Nifi, Informatica, Jira. CERTIFICATIONS:

Microsoft Certified Azure Data Engineer Associate DP-203 Google Data Analytics Certification

PROFESSIONAL EXPERIENCE:

Blackbaud – Sr Data Engineer Jan 2024 - Present

Developed and deployed AWS-based data solutions using EMR, S3, Glue, Redshift, Lambda Function, Step Function, SNS, SQS and DynamoDB.

Automated end-to-end ETL orchestration using AWS Lambda and Step Functions, enhancing data validation, error handling, and workflow efficiency.

Extracted the data in JSON from Amazon S3 using ETL Tools like AWS glue and loaded the data to Amazon Redshift.

Used Glue Catalog with Crawler to get the data from S3 and queried using AWS Athena.

Supported Persistent Key (PK) vendor integration, combining data from multiple external sources (Experian, AnalyticsIQ, CoreLogic) to create a unified identity key, enabling more accurate data modeling and reporting.

Ingested and transformed structured and unstructured data from multiple vendors to support analytics.

Designed and maintained ETL pipelines using Python, SQL, and Pentaho Spoon to support Fundraiser Performance Management (FPM), ingesting and transforming 4,000+ custom client data files daily.

Built and optimized workflows in Pentaho Spoon (KTR/KJB) to support FPM client data loads, monitoring for stuck ETLs and resolving high-priority bugs to improve data reliability and client experience.

Managed and supported the daily load of all our Nonprofit clients data into the FPM product.

Worked closely with Data Analysts, Customer Support, and the FPM Front-End Team to support client data loads and ensure seamless integration between backend data processing and frontend client delivery.

Automated recurring operational tasks and enhanced Redshift deletion processes, reducing manual TOIL and improving overall pipeline reliability.

Fuge Technologies - Data Engineer June 2023 - November 2023

Developed and maintained real-time and batch data pipelines using Databricks, AWS S3, PySpark, Kinesis, and Lambda, ensuring scalable and efficient ingestion of large datasets.

Implemented robust ETL workflows leveraging AWS Glue, Redshift, Step Functions, and EMR maintaining data security and regulatory compliance.

Optimized data lake architecture through effective use of Redshift and Athena, improving query performance and reducing storage costs via tuning and partitioning strategies.

Built interactive dashboards in Tableau and Power BI to visualize key business metrics, enabling stakeholders to derive actionable insights from complex datasets.

Arcane systems - Data Engineer Oct 2022 - May 2023

Designed, developed, and maintained data pipelines for ETL processing ensuring smooth Data Extraction, Transformation and Loading into the Data Warehouse.

Performed Data Migration from On-premises SQL Server to Azure Cloud environment.

Developed Databricks and tasks using PySpark to read data from various sources, perform data transformations in Spark and Databricks, and loaded it into target data destinations.

Utilized Kafka & spark streaming in creating pipelines to extract real time streaming data and stored it in Cassandra and used PySpark to transform the stored data.

Optimized data modeling & data partitioning in Synapse Analytics, resulting in 40% reduction in Query execution.

Adept at Continuous Integration & Continuous Delivery (CI/CD) methodologies using Azure DevOps and Pipelines, streamlining the development and deployment processes for increased efficiency. Accenture Solutions - Data Engineer May 2018 – Sep 2020

Worked on Data Ingestion, Storage and Analysis using Azure cloud services and built Data pipelines.

Implemented data integration by performing extraction and loading of data from Snowflake to Azure Storage.

Worked on ETL and ELT processes using SQL Server Integration Services (SSIS), ADF, Data Lake and performed SSIS configuration for Batch processing.

Used Azure Data Factory for real-time data processing and HDInsight for Big Data Transformation.

Worked on Lambda Architecture using Azure Data platform services like Azure Data Factory, Azure Data Lake, SQL Server, and HDInsight.

Deployed applications with Azure Repos and boards and managed them via CI/CD pipelines built on Azure DevOps.

Improved API performance by employing caching, load balancing, and asynchronous processing, ensuring smooth operation even in high traffic times.

Accenture Solutions - Application Development Analyst May 2017 – Apr 2018

Assisted in the development and optimization of data pipelines using Databricks and Python, enhancing data integration and transformation efficiency.

Conducted data wrangling tasks, transforming raw data into structured datasets for analytics.

Contributed to the management of Delta Lakes and cost-effective cluster utilization in Databricks.

Developed comprehensive documentation and provided training to internal teams, enabling seamless adoption of Azure cloud technologies and services throughout the organization. ASSISTANTSHIP:

Graduate Research Assistant

Department of Information Systems, NIU Aug 2021 – Dec 2021

• Performed Data Collection and Extraction of Data from CMS.gov.

• Taught Undergrad students how to use Tableau to Analyze, manipulate and visualize SC Inventory Data.

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