GEORGE STRATIS
London,UK
Summary
Data Engineer with 6+ years of experience across large-scale data engineering, pipeline reliability, and data quality automation within cloud environments. Strong background designing incremental and near-real-time pipelines, implementing validation frameworks, and driving observability, accuracy, and governance across production datasets in enterprise settings. Experienced mentoring engineers, improving codebase, and advocating for robust, scalable, and automated data quality practices across teams.
Overview
6
6
years of professional experience
Work history
Data Engineer, Service Checker Visualisation
Sky
London, UK
12.2022 - 11.2025
- Led data engineering efforts to ensure quality, reliability, and observability for Service Checker platform.
- Maintained near-real-time pipelines processing 1–3 TB daily, supporting multi-petabyte datasets.
- Designed and implemented a comprehensive data quality monitoring framework across 50+ production datasets.
- Automated data quality checks in ingestion and transformation layers, reducing manual investigation time by 20–30%.
- Administered over five GitHub repositories, enforcing branch protections and CI workflows.
- Integrated CI/CD practices into data pipelines, enhancing deployment reliability and reducing operational steps by over 40%.
- Enhanced SQL test coverage and documentation, resulting in fewer data defects and quicker root-cause analysis.
- Supported cross-functional teams as SAFe Agile Practitioner during story shaping and refinement.
Business Intelligence Developer
Ascential Plc
London, UK
06.2021 - 12.2022
- Built BigQuery-based analytics and Looker models supporting more than 400 users across Finance and Product teams.
- Implemented validation workflows and metric governance improving consistency and reliability of reporting outputs.
- Automated access, audit, and dataset refresh workflows using Python, reducing manual workload by around 40%.
- Translated business requirements into governed and reliable datasets used in self-serve reporting.
Business Intelligence / Insight Analyst
Little Dot Studios
London, UK
11.2019 - 06.2021
- Developed BigQuery data pipelines integrating structured and unstructured media datasets for digital content analytics.
- Standardised performance metrics and validation logic to reduce discrepancies across reporting teams.
- Automated ingestion and quality-assurance workflows, reducing manual validation time by 50%.
- Produced analysis highlighting anomalies and performance deviations across channels and content.
Education
MSc - Operations Research and Analytics
London School of Economics
LondonBSc - Mathematics and Statistics
University of Reading
ReadingSkills
- Data Quality and Reliability: validation frameworks, completeness, timeliness & consistency checks
- Data Engineering: ELT and ETL design, near-real-time ingestion, incremental pipelines, schema design & governance
- Cloud and Big Data: GCP (BigQuery, Pub/Sub, Cloud SQL), high-scale distributed datasets in TB to PB range
- Automation and CI/CD: GitHub admin for 5 repositories, branch protections, workflow automation
- Languages and Tools: SQL, Python, Shell, Control-M, Tableau, Looker, basic Airflow concepts
- Leadership: mentoring engineers, code reviews, documentation standards, SAFe Agile Practitioner
- Collaboration: product alignment, requirement shaping, stakeholder communication
MILITARY SERVICE
Completed military service in Greece and Cyprus, ranked 2nd out of approximately 3,500 cadets at the Hellenic Artillery School. Promoted to Second Lieutenant and led a fifteen-person unit with responsibility for daily operations and communication.
Affiliations
- Motorbikes
- Computer Science
- Travel
- F1
References
References available upon request.
Timeline
Data Engineer, Service Checker Visualisation
Sky
12.2022 - 11.2025
Business Intelligence Developer
Ascential Plc
06.2021 - 12.2022
Business Intelligence / Insight Analyst
Little Dot Studios
11.2019 - 06.2021
MSc - Operations Research and Analytics
London School of Economics
BSc - Mathematics and Statistics
University of Reading