
Data Engineer
Solera Fleet Intelligence Center (FIC) · Jun 2025 – Sep 2026
- Developed and maintained metadata-driven ETL pipelines using Inferyx to ingest, transform, validate, and process fleet and telematics data from multiple source systems.
- Implemented Bronze, Silver, and Gold data layers using Amazon S3, Apache Iceberg, AWS Glue Catalog, and Snowflake, transforming raw source data into standardized and conformed datasets for reliable downstream analytics and reporting.
- Used dbt in Snowflake to create and manage SQL-based transformation models for cleaning, joining, and transforming data across the analytics pipeline.
- Automated Bronze and Silver data validation by developing Python scripts to perform post-pipeline data quality checks, reducing manual validation effort and improving data reliability.
- Monitored and supported scheduled and orchestrated ETL batches across QAE and PROD by tracking execution status, failures, retries, and dependencies, and analyzing batch, control table, Spark, and application logs to troubleshoot and resolve pipeline issues.
- Developed and integrated Python automation scripts into existing incremental batch workflows to support controlled unmasking of designated columns in specific tables based on data-processing requirements.
- Supported Jenkins-based CI/CD and metadata migration across DEV, QAE, and PROD environments, maintaining controlled deployments, version history, and rollback support.

