Looking for a job

Nahom User

@nahomkenna

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Experienced Data Engineer specializing in cloud pipelines, analytics, and real-time data.

United States

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What I'm looking for

I am looking for a role that fosters innovation, encourages collaboration, and offers opportunities for professional growth in cloud technologies.

I am a data engineer with a decade of experience building enterprise-grade data infrastructure and pipelines. My expertise spans cloud platforms (AWS, GCP, Azure), large-scale ETL systems, and modern data tools like Snowflake, Databricks, Airflow, dbt, and Spark. I've led cross-functional teams to deliver real-time analytics, mentored engineers, and implemented MLOps workflows to streamline ML model deployment and reproducibility using MLflow and Databricks.

Throughout my career, I’ve engineered robust data lakes using S3, Delta Lake, and Apache Iceberg, built event-driven architectures using Kafka and AWS Lambda, and optimized warehouse performance across Redshift, BigQuery, and Athena. I've also architected monitoring and orchestration solutions using Prefect, Dagster, Prometheus, and the ELK stack to ensure data reliability at scale.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Shiro Technologies Inc

Jun 2020 - Present (5 years)

Led cross-functional teams to deliver scalable data pipelines and real-time analytics using Spark, Airflow, and Snowflake. Built ingestion systems with Kafka and Kinesis, optimized cloud warehouses (Redshift, BigQuery, Athena), and automated CI/CD with Prefect and Dagster. Enabled BI insights via Looker/Tableau and developed MLOps pipelines with Databricks and MLflow.

AWS Terraform Kubernetes Grafana Helm ArgoCD Python ECS Redshift Snowflake Databricks

Data Engineer

CDI Tech

Feb 2015 - May 2020 (5 years 3 months)

Built and optimized Snowflake pipelines using Snowpipe for real-time ingestion. Improved Redshift and PostgreSQL performance with query tuning. Integrated ML pipelines with Airflow/MLflow, scaled data apps with Docker/Kubernetes, and automated infra via Terraform. Enabled high-throughput streaming with Flink and Spark, and unified analytics via Trino and Databricks.