{ 'Cody Burke': ['ETL/Data Engineer','Operations Engineer'] }

978-***-**** ad3hdx@r.postjobfree.com

As a seasoned professional with extensive experience in data engineering and DevOps, I excel in standing up and expanding data sources which empower both colleagues and clients. My expertise encompasses deploying tools like Python, Pandas, SQL, and AWS, and translating complex data into actionable business strategies. Skilled in interdisciplinary collaboration, I am adept at communicating technical concepts to diverse audiences. I am passionate about creating tools that people look forward to using. Python Pyspark Pandas Pymssql Django Click BOTO3 Prefect Airflow SQL Bash Snowflake Athena Elastic Stack Log Aggregation AWS S3 Lambda ECS ECR Looker Grafana Klipfolio Jira Terraform Git Github Interdisciplinary Communication Public Presentation Project Management Team Training Data Visualization WageUp ETL / Data Engineer 2020 - Present

Led and optimized all data ingest and aggregation processes for SaaS platform, ensuring efficiency and accuracy.

Dramatically enhanced ETL efficiency, slashing run time by over 75% through a strategic migration from Airflow to Prefect 1.0. Significant improvements achieved through parallelizing processes that were previously run sequentially.

Spearheaded a rapid one-month upgrade from Prefect 1.0 to 2.0, achieving a more streamlined system architecture and enhancing ease of team contributions to ETL processes. New system architecture was significantly simplified.

Frequently supported analyst, business, and sales teams with reports, driving sales for both new and existing clients. Introduced self-serve tools for business teams to retrieve commonly accessed data.

Enhanced company-wide workflow and inter-departmental communication by implementing Jira, structuring project planning, and establishing weekly cross-team meetings. This initiative fostered improved collaboration, leading to enhanced customer satisfaction through reduced need for major alterations to products post-launch.

Worked closely with sales team and client analyst teams to rapidly develop and deploy ETL pipelines for new products. New products have seen widespread adoption by clients.

Developed CLI using Click to allow clients simple self-serve access to easily manage data on WageUp GraphQL databases.

Used previous Operations experience to support and debug AWS infrastructure. Reduced costs on several occasions by properly resizing over provisioned resources.

Developed and integrated AWS Lambda and SQL-based monitoring within ETL workflows, triggering real-time alerts to both business and engineering teams for immediate issue resolution. This markedly reduced the occurrence of client-detected errors, improving system reliability and enhancing client trust. Paytronix Analyst / Operations Engineer / Data Engineer 2015 - 2020 Managed SaaS app server health monitoring using Nagios and ELK Cluster. Supported analyst team as the go-to technical expert.

Spearheaded the adoption and implementation of Elastic Stack for efficient log aggregation, significantly accelerating the integration of junior developers into the PagerDuty rotation and alleviating the senior engineering team's support workload.

Introduced Kibana as a tool for app log data visualization, producing critical graphs for daily operational monitoring by the engineering team and enhancing sales demonstrations with key product performance metrics.

Provided comprehensive Kibana training to the engineering team, a pivotal move that reduced the average resolution time of after-hours production incidents from over 3 hours to under 60 minutes.

Created visibility into production system health through Nagios based NOC dashboard, greatly reducing need for Engineering team to update customer support team on status of ongoing production incidents.

Automated internal BI reporting for board and company meetings via Klipfolio, saving executive team hours monthly.

Introduced analyst team to engineering best practices including version control, separation of production and dev environments, DRY principles, config files, logging, and documentation.

Efficiently migrated 12 years of records from an undocumented MongoDB database to Snowflake, enabling SQL-based analysis for the analyst team within two weeks of receipt, crucial for developing a strategic response to COVID-19.