Fernando Sirias

Data Engineer with strong expertise in ETL architecture, data pipeline optimization, and cloud-based data platforms. Specialized in building scalable data solutions using Python, PySpark, SQL, and AWS technologies. Experienced in data warehouse administration, Redshift optimization, and serverless data processing using AWS Glue and Lambda.

Strong foundation in statistical analysis, exploratory data analysis (EDA), correlations, and model attribute engineering to support advanced analytics and machine learning initiatives. Professional with strong analytical thinking, problem-solving mindset, and ability to translate business requirements into robust data engineering solutions.

Sr. Data Engineer at Experian (2024-08 – Present)

Responsible for creation, administration and maintenance of ETL jobs using could architecture in AWS (Glue, Redshift, S3, Lambda, etc) and big data technologies like Spark, SQL. Administrate and maintain data warehouse in AWS Redshift. Version control experience with GitHub and creating clear documentation for ETL pipelines.

• Scrum methodologies (Sprint, Backlog Refinement, Story creation, Estimates)
• Implemented data quality checks, enhancing accuracy by 70%.
• Developed real-time data streaming solutions, increasing responsiveness.
• Utilized cloud technologies, cutting infrastructure costs by 50%.

Data Engineer II at Thermofisher Scientific (2023-07 – 2024-08)

Data Engineering tools: Databricks, Alteryx, SQL, AWS Athena, S3, Power Automate.

• Implemented ETL processes, reducing data processing time by 40%.
• Collaborated with cross-functional teams to align data strategies.
• Developed data models that improved reporting accuracy by 25%.
• Automated data workflows, saving 20 hours of manual work weekly.
• Mentored junior engineers, fostering a culture of continuous learning.

Data Analytics Analyst at Citi (2022-03 – 2023-07)

Extract, transform and load (ETL) data using tools such as Excel, SQL, Oracle, Python, APIs, among others. Work with AWS cloud infrastructure to process data (Glue) and storage (Redshift). Perform data analysis such as correlations, trends, KPIs, statistical analysis.

Automate ETL processes with Python, Excel, Visual Basics, reducing manual work and execution time by 80%. Create custom dashboards for analysis and understanding of real-time and historical data using tools like Power BI and Tableau.

• Storytelling: Present the analysis to stakeholders to understand their data and the behavior of their processes and how to deal with problems based on data.

Dosimetry Technician at ICU Medical (2020-02 – 2021-09)

Responsible of monitoring the sterilization process by measuring the doses received by the product and interpreting the behavior of the process through performance metrics. Use of specialized software (SQL, PowerBI, Minitab, Excel, InfinityQS) for the statistical control of the process and interpretation of graphics.

• Perform multiple validation of products and advanced spreadsheets with success, high quality and in a short period of time, which allowed the company to process new products and comply with the established plan.

Scrum Master Certification – Scrum Alliance (2025 – 2026)

Bachelor in Computer Science – Universidad Hispanoamericana (2019)

Data Science Bootcamp – Coding Dojo (2021 – 2021)

Google IT Support Professional Certificate – Coursera (2020 – 2021)