Data Engineer Big

JAHNAVI MEDIKONDA

***********@*****.*** +1-816-***-**** https://www.linkedin.com/in/mjahnavi9/

SUMMARY

Data Engineer with over 5 years of professional IT experience in building and optimizing scalable data pipelines across GCP, Azure, and Big Data ecosystems like Hadoop and Apache Spark. Certified Google Cloud Professional Data Engineer and Microsoft Azure Data Engineer Associate. Proficient in a wide range of technologies including BigQuery, Dataflow, Dataproc, Azure Synapse, Data Factory, Kafka, and ETL processes for large-scale, high-performance data solutions. Experienced in multiple domains including Finance, Retail, E-commerce, and Healthcare. Skilled in automation, data quality, and cloud-native architectures to enable advanced analytics, BI, and machine learning workflows.

TECHNICAL SKILLS

Cloud Platforms: GCP (BigQuery, Bigtable, Dataflow, Dataproc, Pub/Sub, Composer, Cloud Storage, App Engine), Azure (Data Factory, Synapse, Data Lake, SQL, Databricks, HDInsight), AWS (Redshift, S3)

Big Data & Data Engineering: Apache Spark, Hadoop (HDFS, YARN), Hive, Sqoop, Kafka, Apache Beam, Airflow, Talend, Delta Lake, Apache Pig, MapReduce, Tez, Oozie

Databases & Warehousing: MySQL, SQL Server, Teradata, DB2, Cassandra, Snowflake, BigQuery, Druid

Languages: Python, PySpark, Scala, SQL, HiveQL, Shell Scripting

DevOps & Infrastructure: Docker, Kubernetes, Git, Jenkins, GitLab CI, Terraform

BI & Visualization: Tableau, Looker, Power BI, Microsoft Excel

CERTIFICATIONS

Google Cloud Certified - Professional Data Engineer

Microsoft Certified - Azure Data Engineer Associate

Data Science with Python Certificate - Brain Swig

Cloudera Certified Associate (CCA) Spark and Hadoop Developer – Cloudera

EDUCATION

M.S., Computer Science – University of Missouri – Kansas City, MO (Jan 2022 – May 2023)

B.S., Computer Science – Sir C.R. Reddy College of Engineering, India (Jul 2015 – Apr 2019)

PROFESSIONAL EXPERIENCE

Data Engineer Swiss Re (May 2023 – Present)

Built and maintained multi-cloud ETL pipelines using GCP (BigQuery, Dataflow, Pub/Sub) and Azure (Synapse, Data Factory), optimizing healthcare dataset processing.

Developed automated workflows using Airflow/Google Cloud Composer, ensuring scalability and efficiency across cloud services.

Migrated on-premises databases and data from different sources (Teradata, Hadoop, DB2) to Google Cloud Platform (GCP) using the UDP framework, transforming data with Spark Scala scripts.

Optimized Hive scripts by re-engineering DAG logic to use minimal resources, resulting in high throughput.

Improved the performance and optimized existing algorithms in Hadoop using Spark-SQL, Data Frames, and Pair RDDs, processing terabytes of data daily and contributing to a 15% increase in total users.

Designed Tableau and Power BI dashboards with optimized queries in BigQuery and Synapse to report on store and region-level sales.

Collaborated in an Agile environment and used Git for version control and JIRA for task management.

Big Data Developer Virtusa, India (May 2019 – Dec 2021)

Developed and maintained data workflows using Apache Spark, Hadoop, and Kafka.

Built scalable data pipelines integrating with BigQuery, Dataflow, Pub/Sub, Amazon Redshift, and Snowflake.

Developed data pipelines using Spark, Hive, and Sqoop to ingest, transform, and analyze operational data.

Extensively used Hive for data warehousing, creating tables, partitions, and buckets, and optimizing HiveQL queries for performance.

Contributed to data migration and transformation projects leveraging Azure Data Factory and Databricks.

Participated in CI/CD deployments with Docker, Kubernetes, Git, Jenkins, and GitLab CI.

Hadoop/Python Developer ValueMomentum, India (Jul 2018 – Apr 2019)

Used Spark for interactive queries and processing streaming data, integrating with NoSQL databases for huge data volumes.

Developed automation scripts using Python (Pandas, NumPy) for data handling and API integration.

Analyzed SQL scripts and designed solutions using Scala to implement various data cleansing, validation, and summarization activities.

Resolved performance issues in Hive and Pig scripts by analyzing joins and aggregations.

Designed Oozie workflows for job scheduling and batch processing.

Improved operational efficiency by building reusable and scalable code.

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