Tharun Veeramgari

Professional Summary

• Actively pursuing opportunities in Product Management within an innovative organization, leveraging my 9.5 years of diverse experience in technology roles, along with 1.5 years in a Product Management role.
• Demonstrated leadership as a Lead Data Engineer and Hadoop/Spark Developer over 9+ years, delivering impactful projects and driving technical excellence.
• Previous roles include serving as a SCRUM Lead and Technical Anchor, Technical Product Manager for Product teams, fostering collaboration and ensuring project success.
• Proven adeptness in client engagement, encompassing requirement gathering, system analysis, and the formulation of technical and functional specifications.
• Effective communicator with a proactive approach and a diligent work ethic, adept at guiding teams towards achieving common goals.
• Agile learner with a knack for swiftly assimilating new technologies, poised to thrive in dynamic product management environments.
• Seasoned professional with a strong foundation in software analysis, design, and development spanning Java/J2EE and Big Data technologies.
• Proficiency across a spectrum of tools and platforms including Core Java, Oracle SQL, Netezza, PySpark, HDFS (Hadoop Distributed File System), Hive, Sqoop, AWS (Cloud), and Databricks.
• Acknowledged with the prestigious AWS Certified Data & Analytics - Specialty Developer certification, underscoring expertise in cloud-based data solutions.
• Proficient in IDE tools like Eclipse, IntelliJ, and PyCharm, optimizing development processes and enhancing code quality.

Atlassian CSS – DE (07/2022 - Present)
Project Description:
 CSS DE is a Data Engineering team where we develop Data Ingestion & Analytics Pipelines in Airflow for various business use cases. These pipelines are instrumental in facilitating data analytics for internal dashboards.
Roles:
 Leading a POD as Lead Data Engineer, responsible for interacting with business partners and Data Scientists. Redesigning existing pipelines for enhanced efficiency.
Tech Stack: Airflow, S3 Storage Service, Databricks, Kubernetes, Docker, Python, Shell Script, SparkSQL.

Ford Motor- Enterprise Connectivity (02/2021 - 06/2022)
Project Description:
 Enterprise Connectivity is a platform team focused on developing Data Products to meet various business use cases, primarily for internal marketing and campaigning at Ford Motor. These products enable data transformation and movement to various endpoints, enhancing internal data analytics.
Roles:
 Involved in the development of Data Products, including real-time streaming of data onto HERE OLP Pipelines Platform. Contributed to data transformation and movement processes.
Tech Stack: Hadoop MapReduce, Hive, Spark, Oozie, S3 Storage Service, GCP, Java, Scala, Python, Shell Script, SparkSQL, HiveQL.

Ford Motor-SCA-V (Single Complete Actionable View of a Vehicle) (08/2019 - 01/2021)
Project Description:
 SCA-V is an ingestion platform enabling the extraction of data from Connected Vehicles, facilitating data collection, analysis, and storage. The platform supports the generation of reports for business insights.
Roles:
 Developed ingestion platform components, including Oozie Workflows and business logic. Involved in testing and deployment processes.
Tech Stack: Hadoop MapReduce, Hive, Spark, Oozie, Kafka, Apache Nifi, Java, Scala, Python, Shell Script, SparkSQL, HiveQL.

Standard Chartered GBS (08/2018 - 07/2019)
Project Description:
 Aimed to source and migrate legacy system data into Hadoop Data Lake, enabling data extraction for business teams. The project involved data transformation, validation, and migration processes.
Roles:
 Developed Nifi workflows and custom processors. Collaborated with teams for migration and sourcing activities.
Tech Stack: Hadoop, Hive, Spark, Nifi, Java, Scala, Shell Script, HiveQL.

Nielsen Local TV (11/2013 - 07/2018)
Project Description:
 Nielsen Local TV View (NLTV) is a comprehensive application for television audience measurement, enabling users to analyze viewing trends across different markets. The application supports the creation of custom trade areas for targeted analysis.
Roles:
 Led analysis, design, and development efforts. Collaborated with clients and mentored team members.
Tech Stack: Hadoop, Hive, Spark, Nifi, Sencha GXT, Oracle PL/SQL, Core Java, Netezza, AWS, Shell Script, SparkQL, HiveQL.