Marcus Webb
Senior Data Engineer
Data engineer with 9 years building batch and streaming pipelines that analysts actually trust. I care about boring reliability: idempotent jobs, tested transformations, and lineage you can follow at 2am. Deep on the Spark/Airflow/dbt stack with real production Kafka experience. Looking for a senior IC role owning a data platform end-to-end.
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Experience
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Senior Data Engineer
Freightline
- Own the ingestion platform: 40+ Airflow DAGs moving ~2TB/day from operational Postgres and Kafka into the Snowflake warehouse.
- Rebuilt the shipment-events pipeline as an idempotent streaming job, cutting data-freshness lag from 4 hours to 90 seconds.
- Introduced dbt with 600+ tested models; broke the analytics team's habit of querying raw tables.
- Led the on-call rotation redesign after a quarter with 14 pipeline pages; we now average 2 per quarter.
Data Engineer
Retail Analytics Co
- Built and operated Spark batch jobs aggregating point-of-sale data for 200+ retail clients.
- Migrated the legacy cron-and-bash ETL estate (90 jobs) to Airflow over 9 months with zero missed SLAs.
- Wrote the client-facing data dictionary that cut 'what does this column mean' tickets by half.
Junior Data Engineer to Data Engineer
Datalytics
- Delivered warehouse builds and reporting pipelines for 8 mid-market clients across retail and health.
- Learned the hard way why you version-control SQL — recovered a client's reporting layer from a colleague's laptop backup.
Skills & Self-Assessment
Honest self-assessment — including acknowledged gaps.
Strong
Apache Spark
Airflow
SQL & dbt
Kafka
Python
Moderate
Terraform
Kubernetes
Gaps & Growth Areas
Machine learning
No formal machine-learning experience — I build the pipelines, I don't tune the models
I've never owned a model-training or tuning task end-to-end, so I can't speak with authority on hyperparameter work or model selection tradeoffs.
Honest Fit Assessment
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