Data Engineer

Utilized Airflow to develop ETL pipelines, transforming data from raw formats to readily usable forms for insights.

Employed Cloud Functions, Scheduler, and Sheets to build ETL pipelines that allowed input from less technical stakeholders.

Enhanced data quality and reduced pipeline faults by creating monitoring and alerting dashboards using GCP Cloud Monitoring.

Designed data warehouse tables with a focus on efficiency and cost-effective querying, utilizing partitioning and clustering techniques.

Improved codebase maintainability by applying DRY principles and using Jinja where applicable. Enhanced the CI/CD pipeline by integrating testing for SQL scripts.

Used Terraform to programmatically create and manage GCP resources.

Utilized a combination of EC2 instances and command line to SSH into on-premises machines and transfer CSVs to S3 buckets.

Replaced Airflow with Prefect to transform data, optimizing the workflow management process.

Employed DBT and Jinja to build test scripts and construct the data warehouse.

Used Terraform to programmatically deploy GCP resources.

Used Apache Beam / Google Dataflow to build batch processing pipelines.

Automated multiple ETL pipelines that extracted data from various sources, including cloud storage, Google Sheets, and APIs, specifically targeting Snapchat and Ad Revenue data with outputs to BigQuery tables or dashboards.

Ensured code was unit testable by using Pytest and applying a Test-Driven Development (TDD) approach.

Created dashboards in Google Data Studio (GDS) and set up alerting in GCP to monitor data pipelines. Used Terraform to provision resources on GCP.

Wrote SQL queries for dimensional data modeling in Power BI.

Utilized Python (Pandas) to manipulate datasets for export into Excel.

Created bespoke Power BI reports to provide clear and concise insights into data.

Used DAX language within Power BI to transform and calculate data.

Performed ETL of data from various sources to build data models, typically in Star schema form.

Pulled data from various sources, created relationships between datasets, and modeled the data.

Utilized a combination of Power BI and SQL to create data models and develop insightful reporting visualizations.

Built and took ownership of Power BI apps, monitoring and ensuring access for important stakeholders.

Applied DAX within Power BI to create calculations and measurements on dashboards.

Developed KPI reports and dashboards in Excel using data imported and refreshed from SQL databases.

Extracted data from SQL and performed analysis in Excel using advanced formulas and functions.

Created intelligent web applications for operatives using data imported into Esri ArcGIS.

Wrote efficient and complex SQL queries incorporating pivots, joins, and nested queries.

Amended and manipulated data within the database using SQL queries.

Imported data from MRI and analyzed it in Excel to resolve client issues.

Opened and closed accounting periods on a monthly basis using complex code.

Analyzed data to resolve issues such as unbalanced bank accounts or unlinked child-parent transactions, with backups taken in Excel before troubleshooting.

Performed DBA tasks such as adding or removing users and amending security settings and access.

Mined data to balance accounts in the database.

Searched for missing data on VAT reconciliation reports.