Sriram D

Results-driven Azure Data Engineer with 3+ years of hands-on experience in designing, building, and optimizing scalable data platforms across cloud environments. Proven ability to work with cross-functional stakeholders to translate business requirements into robust data solutions. Strong expertise in modern data engineering tools including Azure ecosystem, Databricks, and big data frameworks.

Adept at building data pipelines, improving performance, and ensuring data governance compliance. Passionate about leveraging data for actionable insights and business growth.

Analytical Engineer - Evotech Solutions

(2025-09)

Collaborated with business stakeholders and product owners to gather requirements, define data architecture, and implement end-to-end data solutions using Azure cloud-based data storage, and Data Engineering services.

• Designed and developed robust ETL pipelines using ADF and Databricks, enabling seamless ingestion of structured and semi-structured data from multiple sources into ADLS Gen2, ensuring high availability and fault tolerance.
• Built and optimized data processing workflows using Synapse Analytics, Spark notebooks, and Microsoft Fabric, improving processing efficiency and reducing execution time for large-scale data transformations.
• Developed data transformation logic using Python and PySpark, leveraging DataFrames, RDDs, and advanced Spark optimization techniques to process high-volume datasets efficiently across distributed systems.
• Implemented Delta Lake architecture using features such as ACID transactions, time travel, schema enforcement, and data versioning to ensure reliability, consistency, and auditability of data pipelines across large-scale systems.
• Integrated external data sources using REST APIs, handling pagination, retry logic, throttling limits, and network failures effectively to ensure reliable and consistent data ingestion processes in production-grade environments.
• Implemented data governance using Microsoft Purview and Unity Catalog, maintaining data lineage, enforcing access controls, and ensuring compliance with enterprise data policies and audit requirements across business domains.
• Developed interactive dashboards and reports using Power BI, enabling business users to gain insights from processed data and supporting decision-making processes across departments with visually rich and dynamic analytics views.
• Automated deployments using Azure DevOps, CI/CD pipelines, ARM templates, and Databricks Asset Bundles, ensuring smooth and consistent release management across environments with reduced deployment risks.
• Provided production support, monitored pipelines using Azure Monitoring tools, resolved incidents, and ensured system reliability by proactively identifying and fixing performance bottlenecks before impacting data workflows.

Data Engineer - EQ Bank

(2023-12 - 2024-11)

Worked closely with business stakeholders and technical teams to gather requirements and translate them into scalable data engineering solutions, ensuring alignment with business objectives across project phases.

• Developed and orchestrated data pipelines using ADF and Apache Airflow, enabling seamless integration and scheduling of workflows across hybrid environments involving Azure and AWS S3 storage systems.
• Built scalable and high-performance data transformation pipelines using Databricks and PySpark, processing large volumes of structured and unstructured data efficiently to support near real-time analytics use cases.
• Designed and implemented data storage architectures using ADLS, Cosmos DB, and Amazon Redshift, ensuring optimized storage, efficient querying, and scalability for both transactional and analytical workloads.
• Implemented Delta Lake architecture to support reliable batch and streaming data processing, leveraging features like schema enforcement, ACID transactions, and data versioning to improve data quality and consistency.
• Developed complex queries and transformations using SQL and Spark SQL, applying optimization techniques such as partitioning, indexing, and caching to significantly enhance query performance and reduce processing time.
• Created business intelligence dashboards and reports using Power BI, providing stakeholders with real-time insights, KPI tracking, and interactive visualizations to support data-driven decision-making processes.
• Enforced data governance and security policies using Unity Catalog, implementing fine-grained access control, data lineage tracking, and ensuring compliance with enterprise data management standards.
• Managed code deployment and integration using Azure DevOps and CI/CD pipelines, ensuring automated testing, version control, and smooth release management across development, testing, and production environments.
• Monitored data pipelines and systems using logging and alerting tools, proactively identifying performance bottlenecks, resolving failures, and ensuring continuous availability and reliability of data processing workflows.

Data Engineer - Bayshore HealthCare

(2023-03 - 2023-12)

Collaborated with business users and analysts to gather reporting and integration requirements, translating them into scalable ETL solutions using SSIS and Azure Data Factory for enterprise data processing.

• Developed and maintained ETL workflows using SSIS and Databricks, enabling efficient extraction, transformation, and loading of large datasets from SAP and other enterprise systems into centralized data platforms.
• Designed and developed OLAP cubes using SSAS, enabling multidimensional analysis and significantly improving performance of reporting queries for business intelligence applications handling complex data analysis scenarios.
• Implemented Delta Lake solutions on ADLS, ensuring reliable data storage with schema evolution, versioning, and efficient handling of large-scale batch and streaming data workloads in scalable distributed environments.
• Developed data transformation scripts using Python and PySpark, optimizing performance through distributed computing techniques and efficient data processing methodologies for processing large structured datasets.
• Created interactive and user-friendly dashboards using Power BI, enabling business stakeholders to visualize trends, monitor KPIs, and perform detailed data analysis with improved data visualization experience.
• Managed source code and version control using Git, ensuring proper collaboration, code tracking, and version management across multiple development teams and environments with efficient branching and merging strategies.
• Optimized SQL queries and ETL pipelines using performance tuning techniques, significantly reducing execution time and improving overall system efficiency and reliability for high-volume enterprise data systems.
• Provided production support and troubleshooting for ETL processes, ensuring timely resolution of issues and maintaining uninterrupted data flow across systems by following standard incident management procedures.

MSBI Developer - GDI Integrated Facility Services

(2022-05 - 2023-02)

Gathered and analyzed business requirements to design and develop reporting solutions using SSRS and Tableau, ensuring reports meet business expectations and provide meaningful insights.

• Designed and implemented ETL processes using SSIS, enabling efficient data extraction, transformation, and loading from multiple enterprise sources.