Lucas A.

Data Engineer

Lucas is a Data Engineer with six years of commercial experience in building and optimizing data solutions. He is proficient in Python, SQL, and NoSQL databases, with extensive expertise in tools like Airflow, Spark, and Databricks.

His experience spans Google Cloud and Power BI, making him adept at handling complex data challenges such as credit data modeling and HR analytics. Lucas has successfully developed data products and automated processes for startups and major financial institutions in Brazil.

His strong business acumen allows him to align data solutions with strategic goals, working closely with business units to drive data-driven decisions. He is known for his ability to tackle complex technical challenges.

Main expertise
  • SQL
    SQL 5 years
  • BigQuery
    BigQuery 3 years
  • dbt
    dbt 3 years
Other skills
  • PostgreSQL
    PostgreSQL 2 years
  • Apache Airflow
    Apache Airflow 1 years
Lucas
Lucas A.

Brazil

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Selected experience

Employment

  • Data Engineer

    TerraMagna - 11 months

    • Development of Data Products: Spearheaded the creation of data products that seamlessly integrate with credit analysis platform applications and services, ensuring the provision of accurate and timely data to business units.

    • Pipeline Development and Data Modeling: Engineered robust data pipelines and performed advanced data modeling to facilitate the effective use of credit and disbursement data. This enabled operations teams to efficiently manage and optimize day-to-day activities.

    Technologies:

    • Technologies:
    • BigQuery BigQuery
    • dbt dbt
    • NumPy NumPy
    • Pandas Pandas
  • Data Engineer

    Stone - 1 year 4 months

    • Credit Data Ingestion and Modeling: Managed the ingestion and modeling of credit data within a lakehouse environment using the Medallion architecture. Key deliverables included loan portfolio monitoring data products tailored for accounting, treasury, and business teams.

    • Process Automation: Collaborated with the product team to automate critical aspects of the credit granting processes. This involved streamlining the data flow from guarantees to the risk team and its associated systems, enhancing efficiency and accuracy.

    • Strategic Indicator Creation: Developed and implemented strategic indicators to support analytics, billing, and various other business units, driving data-driven decision-making across the organization.

    • Data Ingestion Optimization: Led the optimization of data ingestion processes and management practices, focusing on cost efficiency and resource optimization.

    Technologies:

    • Technologies:
    • BigQuery BigQuery
    • NumPy NumPy
    • Pandas Pandas
  • People Analytics Manager

    Creditas - 9 months

    • Leadership and Development: Oversaw the management and growth of all People Analytics teams, ensuring alignment with organizational goals and HR strategies.

    • Development and Integrations: Directed a team responsible for automating and integrating various HR tools, including recruitment and payroll systems, through custom applications developed in Python. This enhanced the efficiency and connectivity of HR operations.

    • Analytics: Led a team focused on data modeling and the delivery of actionable insights. This team provided stakeholders outside HR with comprehensive reports, dashboards, and ad-hoc analyses using Sheets, PostgreSQL, and Metabase.

    • Products and Processes: Supervised a team dedicated to identifying efficiency opportunities within HR processes. This team was responsible for designing innovative products and workflows to streamline HR functions and improve overall operational effectiveness.

    Technologies:

    • Technologies:
    • Pandas Pandas
    • VBA VBA
  • Analytics Engineer

    Loft - 7 months

    • Data Modeling: Modeled the sales and legal data logical layer using SQL, Python, and Databricks with the DBT tool. Enabled the business intelligence teams to create analyses and dashboards in Looker for stakeholder insights.

    • Data Migration Oversight: Managed the migration process between Salesforce environments for the sales and legal teams. Modeled legacy data and data from the new architecture to ensure seamless transition and data integrity.

    • Tool Testing and Feedback: Tested and provided feedback on a new tool developed by the data engineering team for the new data ingestion architecture. Documented data domains and contributed to the optimization of data ingestion processes.

    Technologies:

    • Technologies:
    • dbt dbt
  • Data Engineer

    XP Inc - 1 year 7 months

    • Data Mapping: Mapped HR data across various sources, including SAP, Greenhouse, Mereo, and Mindisght Systems. Ensured comprehensive data integration and consistency.

    • HR Management Tool Integration: Implemented HR management tools for company managers by integrating various data sources (such as compensation, recruitment, goals, and organizational climate surveys) through APIs using batch Python scripts. This integration enhanced data accessibility and streamlined HR processes.

    • Automated Data Extraction: Developed automated routines in Python for extracting data from Greenhouse to support the admissions and recruitment processes, improving data efficiency and accuracy.

    • Power BI Dashboard Creation: Designed and developed the Power BI People Partner Dashboard, providing managerial insights for decision-making and facilitating strategic discussions with business leaders.

    Technologies:

    • Technologies:
    • NumPy NumPy
    • Pandas Pandas
    • VBA VBA
  • Data Science & Analytics

    Guiabolso - 11 months

    • Data Warehouse Modeling and Implementation: Designed and implemented a data warehouse focused on CRM and product data using Databricks and PySpark (an interface for Apache Spark in Python). This architecture supported scalable data processing and integration.

    • Ad-Hoc Analysis: Conducted ad-hoc analyses for the CRM team and assessed campaign performance using Redshift queries and Tableau dashboards. Provided actionable insights to optimize marketing strategies.

    • Recommendation and Conversion Models: Developed recommendation and conversion models for CRM and marketing purposes. These models enhanced targeted marketing efforts and improved customer engagement.

  • Data Science & Analytics

    EY - 1 year 2 months

    • Developed models to predict and explain short-term and long-term hospitalizations for insurance companies.

    • Provided actionable insights to enhance risk management and decision-making.

    • Created comprehensive reports and strategic indicators to help companies identify new strategies and improve process efficiency.

    • Enabled data-driven decisions to optimize business operations.

    Technologies:

    • Technologies:
    • NumPy NumPy
    • Pandas Pandas
    • VBA VBA

Education

  • BSc.Applied mathematics

    University of São Paulo · 2014 - 2019

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