David Ilaya

919-***-**** ad20jq@r.postjobfree.com Garner, NC

SUMMARY

Experienced data engineer with years of hands-on experience in designing, developing, and deploying data solutions using various Azure data products. Proficient in building data pipelines, data lakes, data warehouses and data visualizations using Azure Data Factory, Azure Data Lake Gen 2, Azure Log Analytics, Azure Synapse Analytics and Power BI. Passionate about delivering high-quality and scalable data solutions that meet business needs and drive insights.

QUALIFICATIONS

• Experience with Azure Data Factory to ingest data from various sources, such as Azure Blob Storage, Azure SQL Database, and Azure Synapse Analytics, and to perform ETL (extract, transform, and load) operations using data flows and pipelines.

• Proficient in building data analytic solutions that provide insights into data using Power BI and Excel.

• Proficient in Structured Query Language (SQL) and broad usage of SQL Functions for analytical purposes.

• Performed multiple Data Extraction, Data authentication, Data Cleansing/transformation using Python.

• Proficient in the usage of Azure Data Lake Storage Gen2 to store and access large volumes of structured and unstructured data in various formats, such as Parquet, CSV, JSON, and Delta Lake

• Experience leveraging Azure Synapse Analytics to create dedicated SQL pools and serverless SQL pools for data warehousing workloads, and to create Apache Spark pools for big data workloads.

TECHNICAL EXPERTISE

Programming: SQL, DAX, Python. Data Analytics: Microsoft Excel, Power BI, DOMO. ETL: Azure Data Factory, SQL Server Integration Services (SSIS), Python. Data Storage: SQL Server, Amazon RedShift, Snowflake, Azure Synapse Analytics, Amazon S3, Azure Data Lake Storage (ADLS), Amazon RDS for MSQL. Cloud Computing: Azure, AWS. Methodologies: SCRUM Database Design: Data & Dimensional Modeling. Others: GIT, Azure DevOps, Azure Key Vault, Azure Log Analytics

PROFESSIONAL EXPERIENCE

Data Engineer LabCorp April 2022 - Present

• Designed and developed end-to-end data pipelines using Azure Data Factory to ingest, transform and load data from various sources such as SQL Server, Blob Storage, and API into Azure Data Lake Gen 2 and Azure Synapse Analytics

• Created and configured Azure resources such as Azure Data Factory, Azure Data Lake Gen 2, Azure Log Analytics and Power BI using Azure Portal.

• Developed and scheduled data pipelines using Azure Data Factory to extract data from various sources such as Excel files, CSV, databases, and REST APIs into Azure Data Lake Gen 2

• Automated data ingestion process by creating parameterized pipelines in Azure Data Factory that can handle different source types and formats

• Built interactive dashboards and reports using Power BI to visualize and present data to various stakeholders and clients

• Leveraged Azure Log Analytics to collect and analyze pipeline logs and metrics using Kusto Query Language

• Implemented best practices for data lake storage such as partitioning, compression and hierarchical folder structure to optimize performance and cost

• Created multiple SQL queries against relational databases (SQL Server & Azure Synapse Analytics) to retrieve QA Inspection data for analytical reporting; Created semantic layers using views to transform and cleanse data for reporting purposes

• Developed Domo dashboards and reports to provide insights into the different insurance and client process; this included analytics related to Payment, new account, closure and coverages, Claims; Consolidated data from disparate source

• Developed Power BI dashboards and reports to provide insights into the company’s quality assurance process; this included analytics related to product lot sampling metrics and defect analysis; Consolidated data from disparate sources, configured the model (Relationships and bidirectional filtering), created complex DAX measures / calculated columns, and built interactive visuals.

• Collaborated with business analysts and data scientists to understand data requirements and design data solutions using Azure data products

Senior Analyst Novartis Gene Therapies Jan 2020 – April 2022

• Created and configured Azure resources such as Azure Data Factory, Azure Data Lake Gen 2, Azure Log Analytics and Power BI using Azure Portal.

• Developed and scheduled data pipelines using Azure Data Factory to extract data from various sources such as Excel files, web pages and REST APIs into Azure Data Lake Gen 2

• Performed data exploration and profiling using Python notebooks in Azure Data Factory to identify data quality issues and anomalies

• Integrated Power BI with Azure Data Lake Gen 2 to create direct query connections and refresh datasets automatically

• Designed and developed Power BI reports and dashboards to visualize key performance indicators (KPIs) and trends using various charts, maps and slicers

• Built Excel- based solution that displayed actionable insights information about Products’ Certificate of Analysis data; The reports displayed statistical information (mean, standard deviation, etc.) and comparative analysis among product lots in comparison to test sampling results. Data was extracted from various sources (Applications, files, and relational data sources), and loaded into data models in Excel. Complex transformations were built using Excel functions; Analytical information was displayed using Pivot tables and charts.

• Created Power BI solution that provided insights into product inventory levels, Solution displays inventory levels by products and dates as well as KPI metrics to trigger actions around product restocking (via data-driven alerts)

• Built a reporting database using dimensional modeling techniques to facilitate reporting and analytics around product testing and inventory management.

• Created multiple SQL queries against relational database (SQL Server) to retrieve QA Inspection data for analytical reporting; Created semantic layers using views to transform and cleanse data for reporting purposes

• Created and maintained Python scripts to upload flat files into a relational database for reporting purposes.

Extracted, transformed, and consolidated QA data from disparate data sources (SAP, LIMS and QAD) via python.

• Worked closely with business units to define operational metrics and key performance indicators for reporting purposes.

• Wrote T SQL queries to troubleshoot inaccuracies in Power BI reports and dashboards.

Performed technical research and data gathering to support highly critical projects.

• Created and maintained technical/ business requirements documents according to specs provided by the business.

Analyst Fresenius-Kabi Pharma Aug 2017 – Jan 2020

• Converted complex business requirements into technical documents for easy consumption by team members.

• Created SQL views which contained complex Joins, set operators, and nested system functions, to pull data from SQL Server into Excel for reporting purposes.

• Created multiple Ad Hoc SQL queries related to Medical Fee Schedules, Pricing agreements and contract terms per business analyst requirements as documented in the RFA.

• Conducted weekly Excel reports on HVAC system repairs.

• Built entity relationship models using modeling and normalization methodologies; this model stores organizational data (Copay, Pharmacy, clinical tries registries, financial transactions, and vendor payments).

• Performed multiple research activities to troubleshoot / fix data inconsistences; wrote multiple SQL queries to apply data fixes.

• Built automated solutions (Macros and VBA) to provide seamless data extraction and transformation for excel reports.

• Led efforts to identify key performance indicators and operational metrics that facilitated reporting and data analysis.

• As part of a team, created copay program tracking, ROI measurement, benefit design and coverage gap analysis.

EDUCATION

Bio-Works Certificate Wake Technical Community College Raleigh, NC 2015

BSc., Computer Science Rivers State University of Science & Technology Nigeria 2007 - 2012

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