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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.

Over all 9+ years of professional IT experience and over 5+ years in Data Engineering, and 4+ years in Datawarehouse. Experienced data professional with a strong background in end-to-end management of ETL data pipelines, ensuring scalability and smooth operations. Proficient in optimizing query techniques and indexing strategies to enhance data fetching efficiency. Skilled in utilizing SQL queries, including DDL, DML, and various database objects, for data manipulation and retrieval. Expertise in integrating on-premises and cloud-based data sources using Azure Data Factory, applying transformations, and loading data into Snowflake. Strong knowledge of data warehousing techniques, including data cleansing, Slowly Changing Dimension handling, surrogate key assignment, and change data capture for Snowflake modeling. Experienced in designing and implementing scalable data ingestion pipelines using tools such as Apache Kafka, Apache Flume, and Apache Nifi. Proficient in developing and maintaining ETL/ELT workflows using technologies like Apache Spark, Apache Beam, or Apache Airflow for efficient data extraction, transformation, and loading processes. Skilled in implementing data quality checks and cleansing techniques to ensure data accuracy and integrity throughout the pipeline. Experienced in building and optimizing data models and schemas using technologies like Apache Hive, Apache HBase, or Snowflake for efficient data storage and retrieval for analytics and reporting. Strong proficiency in developing ELT/ETL pipelines using Python and Snowflake Snow SQL. Skilled in creating ETL transformations and validations using Spark-SQL/Spark Data Frames with Azure Databricks and Azure Data Factory. Collaborative team member, working closely with Azure Logic Apps administrators and DevOps engineers to monitor and resolve issues related to process automation and data processing pipelines. Experienced in optimizing code for Azure Functions to extract, transform, and load data from diverse sources. Strong experience in designing, building, and maintaining data integration programs within Hadoop and RDBMS environments. Proficient in implementing CI/CD frameworks for data pipelines using tools like Jenkins, ensuring efficient automation and deployment. Skilled in executing Hive scripts through Hive on Spark and SparkSQL to address various data processing needs. Collaborative team member, ensuring data integrity and stable data pipelines while collaborating on ETL tasks. Strong experience in utilizing Kafka, Spark Streaming, and Hive to process streaming data, developing robust data pipelines for ingestion, transformation, and analysis. Proficient in utilizing Spark Core and Spark SQL scripts using Scala to accelerate data processing capabilities. Experienced in utilizing JIRA for project reporting, task management, and ensuring efficient project execution within Agile methodologies. Actively participated in Agile ceremonies, including daily stand-ups and PI Planning, demonstrating effective project management skills.


  10+ Years Experience in Design, build, and maintain scalable data pipelines to support data integration, ETL processes, and data warehousing.
  Develop and optimize SQL queries to extract, transform, and load data from various sources into datawarehouses.
  Experience in Data engineering encompassing Requirements Analysis, Design Specification, and Testing in both Waterfall and Agile methodologies.
  Experienced Data Engineer with expertise in designing and optimizing data pipelines using Microsoft Fabric. Proficient in integrating and managing large-scale datasets across hybrid environments. Skilled in building real-time data solutions, leveraging cloud-based architectures, and ensuring high-performance data processing with Fabric’s robust analytics and storage capabilities.
  Fluent programming experience with Scala, Java, Python, SQL, T-SQL and Hands-on experience in developing and deploying enterprise-based applications using major Hadoop ecosystem components like MapReduce, YARN, Hive, HBase.
  Experience in Extraction, Transformation and Loading (ETL) data from various sources into Data Warehouses, as well as data processing like collecting, aggregating and moving data from various sources using Apache Flume, Kafka, PowerBI and Microsoft SSIS.
  Proficient in designing and managing REST APIs and integrations using the MuleSoft Any point Platform, with hands-on experience in deploying applications across various environments.
  Hands-on experience with Hadoop architecture and various components such as Hadoop File System HDFS, Job Tracker, Task Tracker, Name Node, Data Node and Hadoop MapReduce programming.
  Experience working with Azure Logic APP Integration tool and Experience working with Data warehouse like Oracle, SAP, HANA.
  Experience in building ETL (Azure Data Bricks) data pipelines leveraging PySpark, SparkSQL and Experience in building the Orchestration on Azure Data Factory for scheduling purposes and Batch Processing.
  Hands-on experience in Azure Analytics Services - Azure Data Lake Store (ADLS), Azure Data Lake Analytics (ADLA), Azure SQL DW, Azure Data Factory (ADF), Azure Data Bricks (ADB) etc.
  Orchestrated data integration CI/CD pipelines in ADF using various Activities like Get Metadata, Lookup, For Each, Wait, Execute Pipeline, Set Variable, Filter, and programming experience on working with Python, Scala.
  Experience working in a cross-functional AGILE Scrum team and good knowledge on Poly base external tables in SQLDW and also involved in production support activities
  Hands-on experience with Amazon EC2, Amazon S3, Amazon RDS, VPC, IAM, Amazon Elastic Load Balancing, Auto Scaling, CloudWatch, SNS, SES, SQS, AWS Lambda, EMR and other services of the AWS family.
  Installed, created, and maintained CI/CD (continuous integration & deployment) pipelines and apply automation to environments and applications. and worked on various automation tools like GIT, Terraform, Ansible.
  Developed web-based applications using Python, DJANGO, QT, C++, XML, CSS3, HTML5, DHTML, JavaScript and jQuery.
  Proficient at developing sophisticated MapReduce systems that operate on a variety of file types, including Text, Sequence, XML, and JSON. Designed, build and managed ELT data pipelines leveraging Airflow, Python, and GCP solutions.
  Experienced with JSON based RESTful web services, and XML/QML based SOAP web services and also worked on various applications using python integrated IDEs like Sublime Text and PyCharm.


To leverage my 5+ years of experience as a Data Engineer to contribute effectively to a dynamic organization where I can apply my expertise in designing, developing, and maintaining scalable data infrastructure and solutions.

Sai Krishna Konduru

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Azure Data Engineer

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Bachelor of Science - Information Technology

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Azure Data Engineer

Bachelor of Science - Information Technology

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