Sridhar V.
Data Engineer
His expertise spans data extraction, wrangling, and building machine learning models, driving effective data-driven decision-making across diverse roles, including data engineer, analyst, and business intelligence developer.
In addition to his technical expertise, he is highly skilled in creating interactive dashboards and visualizations using Power BI and Tableau, which help communicate data insights effectively. Known for his collaborative approach, Sridhar consistently delivers timely engagements, making him a reliable asset to any team.
Main expertise
Apache Spark5 years
Azure Data Factory4 years
CSV11 years
Data Engineering4 yearsExperience4
Senior Consultant
- Successfully led the migration of ETL pipelines from SSIS to Azure Data Factory (ADF), ensuring a smooth transition and improved data integration processes;
- Utilized Databricks notebooks with PySpark and SparkSQL to analyze data effectively, enabling insightful data-driven decision-making;
- Developed Azure Databricks notebooks to retrieve data from various social APIs, including FB, Twitter, YouTube, and Google Analytics;
- Automated the ETL process for loading historical data from FB and Instagram APIs, resulting in significant time savings of 500 hours by eliminating manual effort;
- Built ADF pipelines to execute Databricks pipelines on a scheduled basis, ensuring timely and accurate data processing;
- Created dataflows using ADF V2 pipelines, facilitating seamless data transformation and integration;
- Identified and resolved issues reported by downstream applications, ensuring data integrity and smooth data flow;
- Automated the data load process, reducing manual intervention and improving efficiency;
- Enhanced data load performance from APIs, implementing strategies to optimize data retrieval and processing for downstream applications;
- Leveraged Delta tables in Databricks for performing upsert operations, ensuring data consistency and integrity.
Klarna API
Azure Blob storageAzure Data Factory
Azure SynapseLead IT
- Demonstrated solid analytical skills by understanding requirement specification documents and developing SQL queries accordingly;
- Developed efficient and optimized stored procedures based on the requirements, ensuring adequate data processing and retrieval;
- Conducted proof of concept (POC) to assess the feasibility and benefits of migrating the existing solution to Azure, providing valuable insights for decision-making;
- Identified and implemented performance improvements in existing stored procedures and SQL functions, enhancing query execution speed and overall system efficiency;
- Designed and created a reusable SSIS (SQL Server Integration Services) package to load data iteratively, streamlining the data loading process and improving data integration capabilities.
SSISSenior Software Engineer
- Built an Azure-based data warehouse and database platform to enable fast analysis and decision-making.
- Managed ELT processes, extracting data from SAP HANA, SAP BW, and SAP ERP for database integration.
- Utilized Power BI for data visualization, delivering valuable insights from extracted datasets.
- Designed and optimized data models and structures for efficient storage and retrieval.
- Ensured data quality through cleansing, transformation, and enrichment processes.
- Monitored and troubleshot database performance, resolving issues proactively.
- Collaborated with stakeholders to gather and address reporting and analytical requirements.
- Kept up with industry trends and integrated new technologies to enhance data analysis capabilities.
Azure Blob storageAzure Data FactoryAzure Synapse
IT Analyst
- Developed ETL packages in SSIS for efficient data extraction, transformation, and loading;
- Gathered requirements from stakeholders to ensure a clear understanding of business needs;
- Designed and built Tabular and Multi-Dimensional SSAS cubes for comprehensive data analysis;
- Created visually appealing Power BI reports and dashboards to provide valuable insights;
- Conducted data profiling and cleansing to maintain data quality and integrity;
- Optimized performance of ETL packages, SSAS cubes, and Power BI reports;
- Stayed updated with the latest ETL, SSAS, and Power BI technologies;
- Provided guidance and support to junior team members;
- Collaborated with stakeholders to understand evolving business needs and make necessary adjustments to ETL processes, SSAS cubes, and Power BI reports.
SSASSSISEngineering excellence
All Data Engineers who have applied to Proxify are scored from 0 to 300 on engineering excellence, one of the five parameters we evaluate. This score reflects engineering excellence only, based on interviews, take-home assignments, live coding sessions, and/or on-the-job performance reviews. The curve shows how all evaluated Data Engineers are distributed across that range, where our acceptance threshold for this parameter sits, and where Sridhar stands.
Score 189 · Top 10% of engineers
Certificates 6
Education
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