
Data engineer skilled at cloud computing, automating and scaling processes, and big data management. Demonstrated success in distributed computing, data architecting, and collaborating with cross-functional teams and senior decision-makers to build high impact solutions aligned with business needs.
•Build continuous integration/continuous deployment CI/CD pipelines that promote jobs from development -> test -> production channels (GitLab and Databricks)
•Perform ETL/ELT jobs (using technologies like dbt, AWS Glue, Azure Data Factory, Google Cloud Dataflow) to ingest, transform, and load data into data warehouses and data lakes
•Orchestrate complex workflows using services like AWS Step Functions and Airflow
•Build and deploy environments using container technologies (Docker)
•Utilize various tech stacks including using platforms like Snowflake and Databricks
•Architect streaming and batch pipelines from proof of concept to production
•Design, test, and refactor jobs using Python, R, SQL, PySpark
•Experienced in various ecosystems (AWS, GCP, and Azure)
•Define, document, and maintain architecture of data ecosystem, including data models, data flows, and data governance policies
•Experienced with distributed computing platforms (AWS ecosystem, Google Cloud Platform (GCP), Oracle Cloud Infrastructure)