Early engineering team member developing microservices, SDKs, and backend infrastructure providing modeling tools for sustainable capital planning and infrastructure projects.

Core stack: TypeScript, Python, SQL, Kubernetes, Docker, Postgres/PostGIS, Node.js, GraphQL, gRPC, GCP.

Designed and built weather forecast and wind-wave model pipelines, data processing tools, and APIs

serving global weather data and real-time sensor readings to support internal maritime routing products

and external research partners.

Core stack: Python, Kubernetes, Docker, Airflow, Serverless, SQL, JavaScript, Node.js, Bash, Snowflake, Postgres/PostGIS, Redis, AWS (S3, Lambda, Kinesis, CloudWatch).

Developed data infrastructure, pipelines, and analytics tools for processing product usage and billing data to support strategic decision-making and finance initiatives.

Core stack: Python, SQL, Kafka, Kinesis, Snowflake, Redshift, Postgres, MySQL, Redis, Airflow, Docker, and Databricks.

• Led a project involving cross-functional teams to migrate and backfill the CRM instance with zero downtime, ensuring uninterrupted business operations.

• Automated Kafka topic deployment with integrated data quality monitoring and recency alerts to enhance data reliability and operational efficiency.

• Enabled distributed compute for Airflow workers to make ETL infrastructure more scalable, reliable, and performant; added performance monitoring, logging, and health checks.

[Shut down March 2020]. Built and scaled ETL pipelines to ingest raw metadata from distributed data-lake environments and serve actionable insights that help customers understand the performance of their data products.

Core stack: Python, SQL, Redshift, Elasticsearch, Postgres, Snowflake, Redis, CloudWatch, Django, and Docker.

• Developed data integration pipelines to extract customer warehouse performance metrics and derive insights, ensuring data delivery with measurable quality and under 15 minute latency.

• Reduced cost and latency by optimizing data ingestion workloads, SQL queries, and data transfers.

• Execute database performance benchmarking for internal use cases and against external specifications.