AKHILA MOLUNGURI
Lakeville,Minnesota
Summary
With 7+ years of experience, I specialize in fine-tuning ETL pipelines, advancing data storage technologies, and rolling out real-time analytics in Azure. My expertise includes Data Modeling, Enrichment, Wrangling, Munging, and Transformation, supported by a deep understanding of Spark, Airflow, Hive, Kafka, and Databricks. I excel in orchestrating and transforming data using Azure Databricks and Azure Data Factory (ADF), including developing and integrating PySpark notebooks, and utilizing various ADF activities and Dataflow transformations. Proficient in creating interactive dashboards with Power BI and skilled in Python, Scala, and SQL, I am well-equipped to craft and implement data-driven business solutions. An articulate communicator with strong analytical, problem-solving, and decision-making abilities, I also bring excellent interpersonal skills to every project.
Overview
7
7
years of professional experience
Work History
Azure Data Engineer
Cigna
Minneapolis, Minnesota
05.2024 - Current
- Created numerous pipelines in Azure using Azure Data Factory v2 to get the data from disparate source systems by using different Azure Activities like Move &Transform, Copy, filter, for each, Databricks etc
- Maintain and provide support for optimal pipelines, data flows and complex data transformations and manipulations
- Worked with complex SQL views, Stored Procedures, Triggers, and packages in large databases from various servers
- Used Azure Devops & Jenkins pipelines to build and deploy different resources (Code and Infrastructure) in Azure and Ensure the developed solutions are formally documented and signed off by business
- Worked with team members to resolve any technical issue, Troubleshooting, Project Risk & Issue identification
- Migration of on-premises data (Oracle/ Teradata) to Azure Data Lake Store (ADLS) using Azure Data Factory (ADF V1/V2)
- Designed and created optimal pipeline architecture on Azure platform
- Created pipelines in Azure using ADF to get the data from different source systems and transform the data by using many activities and CI/CD pipelines in ADF using various Activities
- Wrote data ingestion systems to pull data from traditional RDBMS platforms such as Oracle and Teradata and store it in NoSQL databases such as MongoDB
- Built and configured Jenkins slaves for parallel job execution
- Installed and configured Jenkins for continuous integration and performed continuous deployments
- Worked on migration of data from SQL server to Cloud databases (Azure Synapse Analytics (DW) & Azure SOL DB)
- Skilled in monitoring servers using Nagios, Cloud watch and using ELK Stack- Elastic search and Kibana
- Worked on Azure Data Factory to integrate data of both (MY SQL, Cassandra) and cloud (Blob storage, Azure SQL DB) and applied transformations to load back to Azure Synapse.
Azure Data Engineer
Frontdoor
Memphis
07.2021 - 04.2024
- Interact with business stakeholders on requirement gathering and transform data for analytical purposes using appropriate techniques
- Ingested data in mini-batches and performed RDD transformations on those mini-batches of data using Spark Streaming to perform streaming analytics in Databricks
- Worked on various file formats like delimited text files, click stream log files, and JSON files
- Created several Databricks Spark jobs with PySpark to perform several table-to-table operations
- Created pipelines, data flows and complex data transformations and manipulations using ADF and PySpark with Databricks to ingest into Azure Data Lake Storage
- Created datasets, linked services, Azure key vault services in Azure Data Factory
- Created numerous pipelines in ADF to get the data from disparate source systems by using different Azure activities like Move & transform, copy, filter, for each, Databricks etc
- Extensively worked on copy activities and implemented copy behaviors such as flatten hierarchy, preserve hierarchy, and merge hierarchy
- Used ADF activities such as Lookups, Stored procedures, if condition, for each, Set Variable, Append Variable, Get Metadata, Filter and wait
- Used ADF capabilities for data ingestion from multiple sources into Azure Synapse Analytics
- Worked on Microsoft Azure services like BLOB, ADLS, Data Factory and Logic Apps
- Automated jobs using different triggers (Event, Scheduled and Tumbling) in ADF
- Orchestrated data pipelines using Apache Airflow to interact with services like Azure Databricks, Azure Data Factory, Azure Data Lake, and Azure Synapse Analytics.
BI developer
Micron
Hyderabad, India
11.2018 - 05.2019
- Updated functional specifications and technical design documents and explored current OLTP system(s) and devised facts
- Used SQL server Management studio to construct stored procedures, tables, Views, joins and Unions to support data and report requirements
- Involved in requirement gathering, analysis, design, development, change management, deployment and user training
- Worked on building new reports such as cascading reports, custom reports, drill down, drill through reports and parameterized reports and deployed them according to the given requirements
- Research and troubleshoot data/functionality issues related to reports and proprietary applications
- Extract, Transform and Load (ETL) source data into respective target tables as per the requirements by using SSIS services
- Worked on modifying already existing reports and provided production support for the reports as well as performance tuning of the reports
- Proficiency in creating Excel spreadsheets and extensive use of spreadsheets for data comparisons and VLOOKUPs.
MSBI Developer/Microsoft BI Developer
TCS
03.2018 - 11.2018
- Gathered requirements from Business and documented them based on functional specifications
- Used SQL procedures to load the data from other sources like mainframes to ORACLE database
- Worked on OLAP & OLTP including development, testing, and production
- Demonstrated experience with ETL and related technologies, including ability to identify, documenting and analyzing business and data requirements
- Designed and created SQL Databases, tables, indexes, and views based on user requirements
- Highly proficient in the use of T-SQL for developing stored procedures, triggers, tables, Views, Group By, and Joins
- Created User Defined Functions, Stored Procedures, and Triggers
- Highly motivated team player with excellent interpersonal and customer relational skills, proven communication, organizational, analytical, presentation skills
- Experience in using PL/SQL collectables such as Associative arrays, Nested Tables, Arrays
- Worked on performance tuning, testing, and quality assurance.
Azure Data Engineer
Octapharma Plasma Inc.
Charlotte, NC
05.2019
- Utilized Fivetran for efficient and automated data extraction from SQL Server and Oracle Database, leveraging capabilities for both incremental and append-mode extractions
- Designed data extraction strategies using Azure Data Factory, integrating with Fivetran for seamless workflow orchestration from SQL Server and Oracle Database to target destinations
- Managed raw data ingestion into Snowflake’s Source Data layer and ADLS Gen2, using Snowpipe and Azure Event Hubs for efficient loading
- Utilized PySpark with ADLS Gen2 for handling multiple data formats like JSON, ORC, and Parquet, optimizing storage efficiency
- Developed and executed Spark scripts within Azure Databricks for data extraction, transformation, and aggregation, enabling advanced analytics
- Incorporated Python scripts into Azure Data Factory pipelines for versatile ETL tasks, streamlining data processing from SQL Server and Oracle Database
- Utilized DBT and PySpark within Azure Databricks for cleaning, preparing, and transforming data in the Staging Area, optimizing for storage and performance
- Configured DBT models within Azure Synapse Analytics for incremental processing of new and updated records, enhancing analytical workload performance
- Transformed data within the ODS layer to support operational reporting and aggregate ODS (Operational Data Store) data into the EDW (Enterprise Datawarehouse) for analytical processing
- Developed data marts and reporting models with DBT, tailored to specific reporting needs for optimized data access within Tableau
- Implemented strict access control and security policies using Azure Active Directory and Snowflake to protect data
- Generated documentation and maintained data lineage with DBT and Azure Purview, ensuring clarity and transparency across data workflows
- Integrated DBT projects with Azure DevOps and CI/CD pipelines for automated model testing and deployment
- Established monitoring and alerting for data quality and pipeline performance using Azure Monitor, Azure Log Analytics, and Snowflake tools
- Collaborated with reporting teams and maintained data governance standards across all processing and storage layers, ensuring data availability and compliance for analytics and decision-making through Azure, Snowflake, and Tableau.
Education
Skills
- Project Management
- Data Transformation
- Data Modelling & Data Profiling
- Package Configuration
- Reports Generation
- SSIS Packages Development
- Data Extraction
- Dashboard Development
- Supply Chain Management
- Cloud Technologies
- Azure Databricks
- Azure Data Factory
- Azure Synapse Analytics
- Azure Logic Apps
- Snowflake with DBT
- Azure Blob Storage
- Storages
- SQL Server (2012, 2016)
- Azure SQL Managed Instance
- BI Tools
- SSIS
- SSAS Tabular Model
- AAS
- Power BI
- Programming languages
- Python
- Scala
- R
- UNIX Shell Scripting
- PySpark
- Spark SQL
- PL/SQL
- Big-Data Technologies
- Apache Spark
- Hadoop (PySpark, Hive, Pig, Sqoop, Oozie, Zookeeper, Flume, HBase, Yarn, Spark Streaming APIs, Kinesis, Kafka)
- Databricks
- Hortonworks
- Cloudera
- Databases
- MySQL
- SQL Server
- Oracle
- PostgreSQL
- MongoDB
- Cassandra
- DynamoDB
- Amazon Redshift
- Database Management
- SSRS
- Erwin
- Star Schema
- Snowflake Schema
- ETL Tools
- Informatica
- DBT
- Airflow
- Talend
- Apache NiFi
- DataVisualization Tools
- Tableau
- Looker
- Google Data Studio
- Microsoft Excel (advanced)
- Languages
- SQL
- Power Shell
- DAX
- Pyspark
- CI/CD Tools
- Jenkins
- Azure DevOps
- GitLab CI/CD
- Circle CI
- AWS Code Pipeline
- Collaboration Tools
- Jira
- Confluence
- Slack
- Microsoft teams
Timeline
Azure Data Engineer
Cigna
05.2024 - Current
Azure Data Engineer
Frontdoor
07.2021 - 04.2024
Azure Data Engineer
Octapharma Plasma Inc.
05.2019
BI developer
Micron
11.2018 - 05.2019
MSBI Developer/Microsoft BI Developer
TCS
03.2018 - 11.2018