I've been supporting and developing new features for Engine's existing Data Warehouse. Also have been working on the implementation of a Lakehouse Architecture to replace the existing components.

SoLo is one of the leading financial technology companies for underserved communities. Some of the cool stuff I was able to spearhead and contribute to during my time there:- Implementing a raw (bronze) layer to serve as Data Lake- Implementing Snowflake as Data Warehouse backend foundation, and sunsetting the previous stack used for that (MemSQL)- Evaluating and implementing external tools for data integration (Airbyte, Fivetran, Stitch and Matillion among others)- Implementing custom Python pipelines for ingesting data into our Data Lake - Implementing real-time event streaming and processing for some of our Marketing and Growth business scenarios (attribution, audiences, communications, referrals, and loyalty programs among others)- Integrating master dimensional data as well as streaming transactional events with a third-party Promotion Engine (for referrals and loyalty programs)- Integrating master dimensional data as well as streaming transactional events with a third-party Customer Engagement Platform- Evaluating and implementing dbt for reporting and analytics- Implementing dbt- Implementing key Data Quality Metrics, monitoring, and alerting (Soda SQL and Datadog)

I worked in coordination with Data Engineers, Product Owners, and Scrum master to support and enhance our Data platform/product backed by AWS. Some cool stuff we did includes:- Support and extend our Data Warehouse and ETL process- Maintain and develop reports with Python, SQL, and Pandas (compliance, finance, operations, claims, underwriting, risk modeling, Bordereaux, etc.)- Develop PoCs and new integrations to consume our data with external BI and analytics tools (Apache Superset, Power BI, Domo, AWS Athena)- Design and develop the architecture for the product (Data Warehouse, Analytics, Report Builder, Data Audit among others) using Django, Docker and the AWS stack

BriteCore is an enterprise-level insurance processing suite. Built from the ground up using the latest in modern technology, BriteCore combines core, data, and digital solutions into a single platform. We provide out of the box integration with multiple vendors (Quickbooks, MassPrinting, InsVista, Primoris, Mutual Boiler, HSB, and many more). Deployed using the Amazon Web Services cloud, our stack includes:- Python- Django and Pandas (SQLAlchemy as well for some projects)- Git and GitHub- Docker- Continuous Integration with unit, integration and selenium tests- AWS: S3, RDS, CodeBuild, Lambda- DataDog

ENABLE is an SAP gold partner Mexican consulting firm that implements solutions for diverse industries. I worked as part of the Process & Performance team implementing Enterprise Performance Management (EPM) and Business Intelligence (BI) solutions for different customers including stock listed companies to support:- Balanced Scorecard- KPIs and Dashboards- Financial Planning (Driver based planning, rolling forecasts, 5-year budgets)- Financial Consolidation- Compliance reporting (Solvency II and USGAAP)I acquired good knowledge of Financial Planning and Consolidation as well as Data Integration among operational and analytical platforms. Some tools and technologies I worked with include:- SAP Business Planning and Consolidation (7.5, 10, 10.1 MS and NW)- Microsoft Integration Services and SAP Data Services for ETL- SAP Business Warehouse (BW)- SAP Dashboards (formerly Xcelsius)- SAP Disclosure Management- OLAP, MDX and data modeling for Data Warehousing

Worked with a small development team to design and develop a highly interactive tool for learning through inferential graphs using Java, PostgreSQL, JQuery, Hibernate and SVN for version control. I made a lot of requirements gathering with users and the project was managed using an iterative incremental methodology (Rational Unified Process).