Composed complex SQL queries leveraging features such as joins, aggregate functions, subqueries, and set operations to efficiently retrieve and manipulate data. Developed and modified reports based on team needs, producing dashboards and automated reports that enabled teams throughout the organization to make informed decisions driven by data. Processed unstructured data into an analyzable format, conducted data analysis to troubleshoot data-related issues, and contributed to resolving those issues. Collected data from both primary and secondary sources, managed databases and data systems, and identified, analyzed, and interpreted trends or patterns within complex datasets. Executed data management projects and addressed ad-hoc requests as per user specifications, leveraging data management software programs and tools such as Excel and SQL. Designed and implemented tabular data models in SSAS and SSRS to fulfill data analysis needs. Utilized SQL, Python, and Power BI to develop trend analyses and visualizations for customer data analytics, revealing insights aimed at enhancing future revenues. Created custom calculated measures using DAX in Power BI to fulfil specific business requirements.

Took the lead in Establishing and maintaining sophisticated SQL databases for large-scale engineering projects, refining data storage and retrieval processes to enhance efficiency and speed. Integrated SQL databases with three external APIs, automating data synchronization processes and minimizing manual data entry requirements. Managed SQL databases for esteemed clients, ensuring their continuous availability and maintaining data integrity and implemented advanced data encryption techniques within SQL to fortify data security and meet compliance standards for sensitive information. Involved in the design and implementation of data visualizations using Tableau and Power BI, enhancing stakeholders' grasp of intricate datasets, which contributed significantly to improving data accessibility and streamlining decision-making processes. Implemented a rigorous data cleaning and validation protocol, enhancing data accuracy and reliability which was vital in maintaining the integrity of datasets utilized in analytical models and reporting. Took the responsibility of organizing extensive volumes of data, transforming them from raw, unstructured formats into curated, analysis-ready datasets by effectively categorizing data and creating user-friendly data structures. Utilized Python's powerful data analysis capabilities to extract detailed insights, leveraging advanced Excel functions like VLOOKUP and Pivot Tables for swift data manipulations and creating comprehensive analytical reports. Transformed data analysis and reporting processes by introducing advanced Tableau dashboards, resulting in a significant improvement in project data processing efficiency.

Led the implementation of Power BI, resulting in improved project analysis efficiency and significantly enhanced strategic decision-making for critical infrastructure projects. Mastering advanced Excel functions led to a reduction in time spent on data processing and reporting, thereby significantly streamlining project management and operational workflows. Pioneered the use of statistical models and predictive analytics using NumPy and Pandas, a pivotal approach for forecasting project outcomes, identifying risk factors, and revealing opportunities for efficiency gains. Developed comprehensive reports and dashboards using tools like Power BI or Tableau, effectively communicating complex research data to diverse stakeholders. Ensured the precision and reliability of data through rigorous validation and quality assurance procedures in data management, resulting in enhanced data integrity and coherence across network operations and service delivery Effectively managed extensive datasets, ensuring adherence to regulatory standards and internal data governance policies, thereby safeguarding the integrity and security of the data. Collaborated closely with engineering teams to ascertain data requirements and deliver analytical support for experimental design and result interpretation, fostering informed decision-making and optimizing network performance.