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.
