Ruth Jingue
Summary
Data & Business Intelligence Engineer with expertise in Power BI, Azure, SQL, Python, and Microsoft Fabric. Skilled in developing data pipelines, analytics dashboards, and Lakehouse architectures that transform raw data into actionable insights. Proven success in optimizing data systems, improving reporting speed by over 95%, and delivering measurable business impact through KPI-driven analytics.
Overview
4
4
years of professional experience
1
1
Certification
Work History
Data & BI Engineer
Apache Industrial Services
08.2023 - Current
- Designed and managed Azure-based data environments, integrating Microsoft Fabric and Lakehouse architecture to support enterprise analytics and real-time Power BI reporting.
- Developed SQL and Python ETL pipelines automating multi-source data ingestion (Solomon, Skytrax, Procore, SmartBarrel), reducing manual data prep time by 70% (120+ hrs/month).
- Created and maintained interactive Power BI dashboards tracking operational and financial KPIs - including revenue, cost-per-piece, and margin - improving decision-making and profitability by 10% across regions.
- Migrated reporting infrastructure to Microsoft Fabric, cutting dashboard refresh times from 4 hours to under 2 minutes and increasing refresh frequency to six times daily.
- Partnered with finance, operations, and IT teams to define and monitor key performance indicators (KPIs), improving reporting accuracy, transparency, and resource allocation across U.S. and Canadian divisions.
- Automated and unified executive-level data reporting, enhancing visibility and reducing annual costs by approximately $75K.
Data Analyst (BI Team)
Trusted Media Brands
07.2022 - 08.2023
- Automated processing of millions of data rows from Postgres and MySQL, improving real-time reporting and reducing system downtime, saving $20K/month.
- Designed and launched operational Looker dashboards that identified performance opportunities, generating $35K/month in incremental revenue.
- Developed automated data pulls and ETL workflows, saving over 90 labor hours monthly and ensuring data consistency.
- Reconciled and validated over 500K+ misattributed records, ensuring data accuracy for KPIs and performance reporting.
- Collaborated with data science and marketing teams to build reporting infrastructure from the ground up using LookML, SQL, and Python, improving visibility and reporting efficiency.
Fellow Data Analyst
BEPEC
12.2021 - 06.2022
- Partnered with clients to translate business needs into automated Tableau dashboards, saving 10 hours/week in manual reporting.
- Utilized Python to process large streaming datasets, improving data ingestion and processing speed by 85%.
- Delivered insights and ad-hoc reports to executive leadership, driving data-informed strategic decisions.
Education
Bachelor of Science - Computer Science
University of Houston
12.2021
Skills
- Power BI
- Azure
- Microsoft Fabric
- SQL
- Python
- DAX
- Microsoft Fabric
- Power Query
- ETL
- Machine Learning
- REST API
- Data Visualization
- Team collaboration
Hobbies and Interests
- Data Storytelling
- Continuous Learning
- Research
- Travel
- Innovation in Analytics
Certification
Data Analytics with Python
Data Analysis Using Pyspark
Introduction to PySpark
Building for Tomorrow
The "Building for Tomorrow Award" is an award category in Procore's annual Groundbreaker Awards program that recognizes companies using technology like AI, automation, and data to drive innovation and solve construction industry challenges.
Languages
French
Native or Bilingual
Spanish
Full Professional
Timeline
Data & BI Engineer
Apache Industrial Services
08.2023 - Current
Data Analyst (BI Team)
Trusted Media Brands
07.2022 - 08.2023
Fellow Data Analyst
BEPEC
12.2021 - 06.2022
Bachelor of Science - Computer Science
University of Houston