Data Engineer Power Bi

Alekhya Narala

+1-443-***-**** *******.***@*****.*** LinkedIn

PROFESSIONAL SUMMARY

Data data Experienced databases. processing Engineer Strong with with using Python data 3+ Hadoop, warehousing years and Shell Spark, of experience scripting tools Kafka, Redshift, and skills in cloud-Flink, for BigQuery, data based and processing, skilled data Snowflake solutions in ETL along workflows on with and AWS, machine both with Azure, NoSQL Talend, learning and MongoDB, GCP. Nifi, implementation AWS Proficient Cassandra Glue, in and using large-and Airflow. Spark scale SQL MLlib GitLab SKILLS and CI. TensorFlow. Skilled in data visualization with Power BI and Tableau, and CI/CD automation with Jenkins and Big ETL Data Data (Warehousing: Extract, Tools: Transform, Hadoop Amazon (HDFS, Load) Redshift, Hive, Tools: YARN)Google Talend,, Spark BigQuery, Apache (Spark NiFi, Snowflake SQL)AWS, Apache Glue, Apache Kafka, Apache Airflow Flink Cloud Platforms: AWS (S3, RDS, Lambda, Kinesis), Azure (SQL DB, Data Factory), GCP (BigQuery, Cloud Storage) Databases: Data Programming Processing: MongoDB, Languages: Apache Cassandra, Spark, Python Hadoop Redis (Pandas, (NoSQL)MapReduce NumPy, ; MySQL, PySpark)PostgreSQL,, SQL, Shell SQL Scripting Server, Teradata, (Bash) DB2 (Relational) Data Governance Tools: Apache Atlas

Machine Machine Business Learning Learning Intelligence Algorithms: Tools: (BI) Spark Tools: Linear/MLlib, Power TensorFlow Logistic BI, Tableau Regression, Decision Trees, Random Forest, K-Nearest Neighbors (KNN) Continuous Version Collaboration Control: Integration/Tools: Git, GitHub Jira, Continuous Confluence Deployment (CI/CD): Jenkins, GitLab CI, GitHub Actions WORK EXPERIENCE

Data Engineer

Goldman Sachs Global Jan 2023 – Present

● ● ● ● Improved job Deployed Designed of Transitioned data runtimes, daily, and predictive data reducing legacy enabling implemented ingestion ETL models operational faster systems workflows ETL data-to analyze pipelines to driven downtime Snowflake, with user Apache decisions. with behavior, by Azure 25%increasing Spark . Synapse increasing and scalability Delta and targeting Lake, Databricks, by significantly 30% accuracy and achieving reducing enhancing through 99% operational PyTorch uptime processing and while costs speed Keras processing through and frameworks. reducing cloud- 5TB+

● ● based Upgraded and Advanced targeted faster optimizations. marketing SQL customer data query retrieval. strategies. segmentation performance models, and optimized driving database a 15% increase schema, in resulting revenue in by a 35% leveraging increase machine in query learning execution insights speed for

● Implemented response time and a real-enhancing time monitoring data reliability. system using Apache Kafka and AWS Lambda to detect data anomalies, improving incident Data Engineer

Coforge Jan 2020 – Jul 2022

● Revitalized data integration workflows in Snowflake, reducing data duplication by 40% and increasing real-time data

● ● ● ● accessibility Structured data Developed insights. Built Enhanced coherence and deployed performance a RESTful robust by across 20% machine Snowflake APIs through the and organization. to scalability learning streamline Kafka-schema driven of models data integrating data processing ingestion. access, using over Scikit-boosting workflows 100 learn datasets, reporting to on improve AWS reducing infrastructure, efficiency predictive data and retrieval accuracy enabling reducing times efficient for lag key by time handling performance 30% for and of more millions improving metrics. timely of records daily and reducing processing time by 20%.

● Streamlined integrations. ETL workflows with Apache Airflow and Python, reducing manual tasks and strengthening data accuracy across multiple E DUCATION and CERTIFICATIONS

Master’s in data science University of Maryland, Baltimore County Bachelor’s Microsoft Certified: in information Azure technology Data Engineer Malla Associate Reddy Engineering (DP-203) College

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