Marcos Samuel Santos Ouriques

Data Engineer graduated in Data Science-Big Data with 10+ years of experience in Data Engineer, Data Science, Data Analysis and Business Intelligence. I always apply the skills that I acquired during my career, being hard skills as: Database, SQL Server/Snowflake/MySQL/Databricks, programming languages (Python, Scala, C/C++, C#, Java, PySpark), Data Mining and Cloud Computing, Machine Learning, relational algebra, statistics, data quality.

Or soft skills such as: Collaboration, empathy, anticipating problems and demands and working under pressure; - Being curious and constant learning, it is interesting to find an environment with diverse challenges, delivering new impact results for different business areas and resulting in the development and achievement of new skills, always using data to leverage it.

Data Engineer at DoorDash. (2023-05 – Present) • Using Databricks, Spark, SQL Snowflake and Python on Airflow, Create scalable pipelines (ETL) and Single Source of Truth Tables to provide the Analytics team with correct and refreshed information properly scheduled and automated. Those tables had information about stores, clients, texts and model rules. All of them required proper discussions with data providers and stakeholders to ensure data quality and the output is useful for the final client as inputs for data science modeling, experiments and LLM as ChatGPT.

Intense SQL coding was applied to get great performance, data quality and modeling, saving process and re-work time.

• Migrate ETL (DAGs) from Snowflake to Databricks, rewriting them with sensors, operators and redesigning queries as required. They were done inside Airflow and Github (with CI/ CD process) and were required to follow data testing, ensuring minimal or no impact for each DAG migrated. They improved Airflow performance and maintainability, better detailing logs and task runs. These migrations achieved at least 20% cost savings.
• Develop Ad Hoc requests from analytics teams to create and schedule ETLs, using DAGs, sensors and operators to import data from different sources such as Google Sheets and Snowflake, or delivering to S3. They improved analytics team routines and Sigma dashboard performance.
• Update Sigma dashboards with newly created tables, replacing analytics team tables and test numbers as required.
• Perform SQL Query Optimizations reducing run time by 40%. Data Scientist | Data Engineer at TEx (2021-11 – 2023-05) • Implement a deductible pricing machine learning model using random forest model in Azure ML Studio that suggests deductible pricing according to car and driver's features, doing required Data Analysis over input data.
• Implement APIs using Azure API Management that call several machine learning Models along with required inbound and outbound politics.
• Implement a recommendation model using client clustering that will suggest other cars when a client requests an insured quotation.
• With a team and other areas inside the company, developed Residential Insurance Analytics, extracting data from MongoDB and do the ETL over JSON data processes using Python to save it in MySQL.
• Raise a Databricks with Spark environment inside Azure, allowing historical insurance TEx calculation data to be processed in Delta/Parquet format, teaching the team what Databricks is, its architecture, how it would align with company needs.
• Using Power Virtual Agent and Power Automate, create a chatbot that will receive a quotation, send it to the appropriate API and retrieve the predicted value.
• Using Azure Automation Account, create a Powershell Workflow that pause, resume, upgrade and downgrade PBI tier, doubling dashboards availability with only 20% cost increase. Data Scientist | Data Engineer at Propz (2020-09 – 2021-10) • Monitor, support, improve and refactor notebooks in Spark Scala that generate the set of offer recommendations for each Carrefour customer in an orderly manner according to importance and daily process.
• Documentation and clarification of business rules for these notebooks according to customer queries.
• Implementation of measurement notebook in Spark Scala for thematic campaigns according to customer definitions extracting information from Snowplow.
• Cohort analysis of registrations in the loyalty program and purchase activation for LeBiscuit customers.
• Implementation in Apache Superset of the panels and notebooks for historical and current calculations in Spark Scala de Churn, contribution margin and average expected value (LTV) for AbasteceAí - Ipiranga. Data Analyst | Data Engineer | Intern to Senior Consultant at Urban Science (2014-10 – 2020-09) • Designed and implemented SQL-based data pipelines to configure and process all Nissan Brazil market data, ensuring accurate alignment with client requirements and geographical rules identifying new open point potential locations • Automated dealer performance management processes in SQL Server, providing Nissan Brazil with comprehensive network KPIs across all dealerships.
• Collaborated with international teams to configure and maintain the proprietary network analysis tool (Ni2), enabling seamless execution of studies and optimized data workflows.
• Validated and consolidated datasets from various sources, using SQL and Excel to ensure data quality and integrity for client projects.
• Conducted comprehensive network planning analyses for automotive brands (Audi, Nissan Brazil, FCA Argentina), delivering actionable insights to optimize dealership networks.
• Defined market areas, established performance KPIs, and measured network efficiency to identify opportunities for growth and improvement.
• Created demographic and performance-based insights to identify key market gaps, guiding clients toward optimal solutions for network expansion.
• Visualized analytical results through presentations, ensuring alignment with client expectations and contract deliverables.
• Partnered with clients during project initiation to define data requirements, ensuring analytical objectives were met effectively.
• Supported Audit System connecting local client teams with International Support teams from USA and Europe when necessary.

Information Technology

Technician at Brazilian National Bank - Caixa Economica Federal (2010-05 – 2013-05) • Using SQL, extract and process information on the definition of urban conurbation from the document sent by the regulatory department, reducing undue bills complaining.

• Assisted in the implementation of a new networks contract throughout Brazil • Cared about the process of receiving, validation, and treatment of Toll-Free bills.

Post Graduate in Big Data MBA, Data Science – FIAP (2017 – 2018)

Exchange Program in Computer Engineering – Tennessee Technological University (2013 – 2014)

Bachelor Degree in Computer Communication Network Engineering – University of Brasília (Universidade de Brasília) (2007 – 2014)