• Technical lead for full-stack process to save user & application data from our website to a database and transform it for internal use. Project management included systems design, working with the team to get agreement on the best path forward, creating cards for the team, working with the team 1:1 as a mentor, and reporting progress to management & internal stakeholders

• Technical lead for data engineering project to transform BigQuery data for internal use, including mentoring data analysts to provide necessary skills for continual maintenance of the data pipeline

• Built & maintained back-end AWS infrastructure using sst & aws-cdk to build lambdas, queues, APIs, databases, security groups, policies, roles, EC2 instances, Cloudfront distributions, hosted zones, & more

• Built & maintained front-end React code which supports an application for users to apply for government funding for their internet service

• Championed best practices by creating a tech plan process, documenting APIs, implementing SSO for our AWS sign-in, creating best practices for unit & load testing, linting, routing logs to DataDog for alerting, creating PR templates for our repositories, using Github actions for deployments, and implementing feature flags

• Enhanced organizational culture by participating in DEI Council & Social Committee, by working on initiatives to support the organization and planning social events

• Built & maintained a data pipeline orchestrated with Airflow, which utilizes dbt, Databricks, and assorted custom Python jobs, such as an hourly sync from OLTP databases into Redshift database

• Built & maintained a data lake to ingest semi-structured data like CSVs and logs utilizing Retool for ingestion, S3 for storage, Lambdas for validations and transformations, and AWS Glue and Spectrum for transforming data into Redshift database

• Built & maintained Looker views, explores and dashboards written in LookML for various stakeholders

• Migrated complex SQL logic previously stored in Looker PDTs or Spark jobs into simplified, best practice dbt transformations structured with facts and dimensions

• Ensured best practices of new and existing data products by utilizing linting, unit testing, dbt tests for data quality, Github actions for deployments, and testing outside of production environment

• As co-chair of Diversity and Inclusion Working Group, led company-wide discussions around sensitive topics and planned culturally relevant events

• Developed our analytics web product’s front and back end by pulling the data in from a Snowflake database using node.js and creating visualizations with d3.js, which includes a login and user specific data pull.

• Designed and built the data architecture within Snowflake by creating an ETL pipeline that transformed public data sets into final metrics that fed into our website.

• Managed our website’s server as well as the storage of large datasets using AWS services.

Designed and implemented ELT data pipelines which automatically pulled data through multiple transformations.

• Utilized python and Google Cloud Functions, Storage, and Pub/Sub to transform PDF invoices into line items of data which were then flagged for cleanliness based on historical costs and inserted into a BigQuery database.

• Designed and implemented automated triggers in a mySQL database to take in a user’s inputs and display complex financial calculations to the client facing website.

• Built automated triggers in a Postgres database to aggregate data from multiple sales channels and transform into holistic sell-through metrics.

• Migrated a client off of legacy systems Mode and Postgres by implementing all one-off calculations into a single source of truth within a new Snowflake database and building a series of dashboards in Tableau.