Joseph Enser

Improved MLB's league-wide data infrastructure supporting league departments and 30 clubs, raising scheduled-run success from approximately 98.1% to 99.4% across 38 Apache Airflow DAGs. Optimized 12 BigQuery transformations and modernized 24 dbt models, cutting runtime from approximately 74 to 31 minutes while strengthening data quality.

Standardized batch and API ingestion pipelines on GCP for approximately 70 internal users, cutting source onboarding from approximately 8 to 4 business days with reusable Python and Airflow patterns. Implemented deterministic backfills across 14 datasets using partitioning, schema normalization, retry handling, and idempotent Python loads.

Centralized PlanSource's benefits-administration warehouse for 35 PowerBI and business users, improving data freshness from 24 to 4 hours across 16 feeds with Fivetran, Python, Snowflake, and incremental ELT.

Modernized Discover's enterprise customer and operational-data transformations for approximately 60 internal consumers, cutting Spark runtime from approximately 5 hours 20 minutes to 2 hours 5 minutes using PySpark and Spark SQL. Standardized Apache NiFi ingestion with parameterized schema validation across ten recurring feeds into the Hadoop data lake, improving consistency and maintainability fo

Consolidated Discover's operational and collections reporting for approximately 45 recurring users, reducing weekly preparation from approximately 6 hours to 1.5 hours by replacing 18 reports with four Tableau dashboards. Defined Teradata SQL, dimensional modeling logic, metric definitions, reconciliation queries, and exception tables across 26 source tables to standardize trusted operational repo

Bachelor's Degree in Finance from the University of Utah, completed in 2013.