Jaseem Baari Email & Phone Number

Atlanta Metropolitan Area

• As a data engineer, I implemented Azure Synapse for unified analytics, integrating both structured and unstructured data seamlessly.• Executed T-SQL queries and deployed serverless SQL pools in Azure Synapse for cost-effective analytics as a data engineer.• Orchestrated scalable and flexible data warehousing solutions to handle large datasets effectively in my data engineering role.• Ensured data security and compliance, and collaborated within Synapse Studio to streamline data pipeline management and monitoring as a data engineer.• Implemented Snowpark UDFs for custom data transformations and contributed to workspace collaboration, fostering teamwork and insights sharing as a data engineer.• Leveraged extensive AWS cloud platform experience and applied Spark RDD, DataFrame, DataSet, and Spark Streaming knowledge in my data engineering projects.• Developed Spark applications using Python to handle data from various RDBMS and streaming sources, and improved existing algorithms in Hadoop as a data engineer.• Employed Spark Context, Spark-SQL, Spark MLib, and Spark YARN effectively, and used Spark Streaming APIs for real-time data transformations as a data engineer.• Developed a learner data model using Kafka for real-time data ingestion to Cassandra and crafted a Kafka consumer API in Python as a data engineer.• Processed XML messages using Kafka, developed preprocessing jobs with Spark DataFrames to flatten JSON• Experienced in live real-time processing and core job execution using Spark Streaming with Kafka, and migrated an existing on-premises application to AWS as a data engineer.• Maintained the Hadoop cluster on AWS EMR, loaded data into S3 buckets using AWS Glue and PySpark and configured Snowpipe to pull data into Snowflake tables as a data engineer.• Managed data storage in Snowflake's staging area, created ODI interfaces for Snowflake DB, and consolidated Data warehouses into Amazon Redshift, highlighting strategic data engineering initiatives.

Sunnyvale, California, United States

• As a data engineer, I demonstrated proficiency with Azure tools such as HDInsight, DataLake, Databricks, Blob Storage, and Synapse, orchestrating complex data workflows and enhancing data processing pipelines.• Designed and deployed data pipelines using DataLake, Databricks, and Apache Airflow, enabling advanced machine learning solutions and empowering team collaborations.• Integrated Snowpark with Azure Data Factory for data processing, focusing on performance tuning to enhance query efficiency and overall data handling.• Managed integration projects using Azure Data Factory, merging data from MySQL and Cassandra with Azure cloud sources, and optimizing data flow back to Azure Synapse.• Utilized Spark Scala for real-time data mining and insights, configured Spark Streaming to receive data from Apache Flume, and processed extensive datasets in Azure Blob storage using Databricks.• Optimized existing Scala code and enhanced cluster performance using Spark Streaming API; applied business transformations and data cleansing using Databricks Notebooks.• Developed Python scripts for ETL pipelines and directed acyclic graph (DAG) workflows with Airflow and Apache NiFi, managing task distribution on celery workers to enhance service communication.• Monitored Spark clusters using Log Analytics and Ambari Web UI, transitioning log storage from Cassandra to Azure SQL Datawarehouse to improve query performance.• Developed data ingestion pipelines on Azure HDInsight Spark cluster using Azure Data Factory and Spark SQL, handling diverse data sources including Cosmos DB.• Designed custom input adapters with Spark, Hive, and Sqoop to analyze data from Snowflake and MS SQL, showcasing a broad skill set in an environment using AWS EMR, S3, Glacier, CloudWatch, HDFS, Hive, Kafka, Python, PySpark, Linux, Airflow, Jenkins, Oracle, Git, Tableau, DynamoDB, Teradata, QlikView, and REST API.

Sunnyvale, California, United States

• As a data engineer, I gained experience working on projects involving machine learning, big data, data visualization, and R and Python development, along with SQL.• Performed exploratory data analysis using NumPy, matplotlib, and pandas, applying my data engineering expertise.• Expert in quantitative analysis, data mining, and presenting data to uncover trends and insights as a data engineer.• Analyzed data using Python libraries including Pandas, NumPy, SciPy, and Matplotlib, demonstrating my analytical skills in data engineering.• Configured AWS Identity and Access Management (IAM) Groups and Users to enhance login authentication, as part of my security management responsibilities as a data engineer.• Conducted systems design, feasibility, and cost studies, recommending cost-effective cloud solutions such as AWS from a data engineering perspective.• Created complex SQL queries and scripts to extract and aggregate data, ensuring data accuracy and effectively translating business requirements into clear specifications as a data engineer.• Prepared high-level analysis reports using Excel and Tableau, providing feedback on data quality including identification of billing patterns and outliers as a data engineer.• Worked with various visualization types including Maps, Density Maps, Tree Maps, and other chart types in Tableau, enriching data presentation capabilities as a data engineer.• Handled sort & filters in Tableau, managing Basic Sorting, basic filters, quick filters, context filters, and filter operations, showcasing my technical skills in data engineering.• Read data from various sources such as CSV files, Excel, HTML pages, and SQL, performed data analysis, and wrote to data sources including databases, employing my data engineering skills.• Worked within an environment that included Azure HDInsight, Databricks, DataLake, CosmosDB, MySQL, Snowflake, MongoDB, Teradata, and other technologies, reflecting my broad experience as a data engineer.

San Francisco Bay Area

• As a data engineer, I extensively used Informatica Client tools including Power Center Designer, Workflow Manager, Workflow Monitor, and Repository Manager.• Extracted data from various heterogeneous sources such as Oracle and Flat Files, leveraging my expertise in data integration.• Developed complex mappings using the Informatica Power Center tool, a critical component of my data engineering tasks.• Executed data extraction from Oracle, Flat files, and Excel files, and performed complex transformations including joiner, expression, and update strategy to load data into target systems as a data engineer.• Created Sessions, Tasks, Workflows, and Worklets using Workflow Manager, reflecting my workflow management skills.• Collaborated with a Data Modeler to develop STAR Schemas, enhancing our data warehousing solutions as a data engineer.• Involved in analyzing the source feed in the existing CSDR database to ensure data integrity and accuracy.• Handled high volumes of daily Informatica workflow migrations, showcasing my capability to manage large-scale data operations.• Reviewed Informatica ETL design documents and worked closely with development teams to ensure adherence to correct standards, a key responsibility in my role as a data engineer.• Created new repositories from scratch, managed backups, and performed restores, maintaining robust data management systems.• Managed user groups by working with groups, roles, privileges, and assigned them to each user group to enhance security and operational efficiency.• Knowledgeable in code change migration from Development to QA and QA to Production, ensuring smooth transitions in project lifecycles.• Worked on SQL queries to query the Repository DB, identifying deviations from company's ETL standards for various objects created by users, enhancing compliance as a data engineer.