I'm thrilled to see you here 😊! You've stumbled upon my profile, so you're likely eager to dive into my professional skills and career adventures. Thanks 🙏 for stopping by — let's connect and create something amazing together! ♦As an accomplished AWS Data Engineer with nearly 6 years of hands-on experience, I specialize in creating and implementing robust data warehousing solutions, cloud computing, and seamless ETL processes. My professional journey includes significant contributions to high-profile clients such as Synchrony Financial and Accenture. At Synchrony Financial, I’ve designed enterprise data lakes and developed real-time data transformations using AWS Glue, Spark Processing, Kinesis Streaming, and other AWS services, ensuring data-driven decision-making and actionable insights. My technical acumen extends to managing AWS EMR clusters, automating processes with AWS Lambda and Step Functions, and handling large-scale data ingestion and transformation. Recognized for my exceptional work ethic with awards like the Accenture Celebrates Excellence (ACE) award and the Rising Star Award, I bring a proven track record of delivering high-quality results. My skill set spans SQL, Python, PySpark, and a deep understanding of both dimensional and relational data modeling. I thrive in Agile environments and am proficient with version control systems like Git and continuous integration tools such as Jenkins. My expertise in AWS services—ranging from S3, EC2 to Redshift—enables me to tackle complex data engineering challenges effectively. Let’s connect to explore how my skills can drive success for your organization.💡★Just a Thought★: Securing a job is just the beginning of the journey; the real magic happens through relentless learning 🎯. I’m passionate about continually enhancing my skills and tackling new challenges. Let your knowledge light the way to new opportunities. Let’s connect and see how we can transform learning into impactful results together! 🤝
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Aws Data EngineerSynchrony Jul 2023 - Sep 2024Frisco, Texas, United States• Skilled in utilizing Python and Pyspark to create delta files from full files and designing Enterprise Data Lake solutions on AWS. • Developed ETL processes with AWS Glue to move data from various sources to Redshift. • Utilized a range of AWS services including S3, EC2, Athena, and Kinesis for data processing and model deployment. • Automated ETL processes with Lambda and Glue, monitored with CloudWatch, and analyzed data using Athena and QuickSight. • Implemented streaming data solutions with Kinesis services and stored output in S3, DynamoDB, and Redshift. -
Instructional Design AssistantC. T. Bauer College Of Business (University Of Houston) Jun 2022 - May 2023Houston, Texas, United States• Blackboard course build, support, and Grade Center Management • Respondus Exam build, deployment, and monitoring • Zoom support • Kaltura platform migration support and Interactive quiz support • Course video management support -
Data EngineerAccenture Jan 2019 - Dec 2022Hyderabad, Telangana, India• Worked with various data streams such as JSON, XML,CSV and DAT and implemented the Data Lake theory.• Designing ETL processes using AWS Glue to load data from Flat Files, Oracle and Excel files to target Oracle Data Warehouse database. Majority of the infrastructure is hosted on AWS and uses AWS EMR • Involved in migrated existing on-premises application to AWS and used AWS services like EC2 and S3 to process and store small data sets.• ETL pipelines were developed and deployed using Python, SQL, Spark, and Pyspark to ingest data and update relevant databases.• Used Spark for each data update in a DynamoDB table, AWS Lambda was used to execute data validation, filtering, sorting, or other transformations, and the converted data was loaded to another data store AWS S3 for raw file storage.• Involved with Spark for quick data processing. Spark Shell and Spark Standalone clusters were also used.• AWS EMR was used to convert and transport huge volumes of data into and out of other AWS data storage and databases, such as Amazon S3 and Amazon DynamoDB.• AWS Identity and Access Management (IAM) was used to assign rights, policies, and responsibilities to users and groups. -
Etl Data EngineerAccenture May 2017 - Dec 2018Hyderabad, Telangana, India• Involved in migrating from on-premises VMs to AWS cloud infrastructure, utilizing EC2 for computing, S3 for scalable storage, and RDS for managed databases• Utilized AWS Step Functions to orchestrate and automate complex workflows, enhancing workflow efficiency and ensuring reliable execution• Integrated AWS Lambda functions with S3, Glue, and SNS to automate data processing pipelines, ensuring efficient ETL operations and timely notifications• Utilized AWS Athena to write and execute complex SQL queries on data stored in Amazon S3, enabling efficient and scalable data analysis and reporting• Integrated AWS S3 for storage, AWS Glue for ETL, Amazon Redshift for data warehousing, and AWS Lambda for serverless compute to automate data pipelines, enabling efficient ingestion, transformation, and analytics workflows• Development of Ab Initio graphs.Pre-processing of data and loading source files to S3.• Developed DynamoDB tables for streamlined key-value storage, employing primary keys and secondary indexes to optimize data access and query efficiency
Venkata S Education Details
Frequently Asked Questions about Venkata S
What is Venkata S's role at the current company?
Venkata S's current role is Data Enthusiast | AWS Data Engineer | Glue | Spark | Python | SQL | Databricks | Top Voice in Data Engineering & Warehousing 🗣️ | 1x AWS Certified.
What schools did Venkata S attend?
Venkata S attended University Of Houston, Gandhi Institute Of Technology & Management (Gitam) University, Visakhapatnam.
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Venkata S.
Louisville, Ky -
Venkata S.
#Software Developer | Java | Spring | Sql | Rest Api | Microservices | Docker | Kubernetes | Aws Cloud Services Certified Developer | Open To Work On #W2San Jose, Ca
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