K

Ken Odegard

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Houston, Texas, United States

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Résumé

Jobs verified_user 0% verified
  • Benchling
    Data Solution Architect
    Benchling
    Oct 2022 - Current (3 years 9 months)
    Architected and deployed real-time data streaming infrastructures using Apache Kafka, Apache Flink, and AWS Kinesis, enabling 99.9% uptime for data pipelines and improving supply chain visibility and operational responsiveness by 35%. Designed and implemented scalable, cloud-native data architectures across AWS, Azure, and GCP, integrating Amazon Redshift, Google BigQuery, Azure Data Lake, Databricks Lakehouse, and Snowflake, leading to a 50% reduction in infrastructure costs and enhanced performance elasticity. Led end-to-end migration of on-premise data warehouses to modern cloud ecosystems, leveraging Snowflake, Delta Lake, and Databricks, resulting in 60% improvement in query performance and 70% decrease in maintenance overhead. Enginee
  • Expero
    Senior Data Engineer
    Expero
    Aug 2019 - Sep 2022 (3 years 2 months)
    Developed and optimized large-scale data pipelines using Hadoop, Spark, Kafka, and Hive, significantly improving data processing speeds. Designed and implemented distributed storage solutions using HDFS, HBase, and Amazon S3, enhancing data accessibility and fault tolerance. Automated ETL workflows with Apache NiFi and Airflow, ensuring seamless data ingestion and transformation across cloud platforms. Collaborated with data science teams to deploy and maintain machine learning models on Databricks and MLflow, improving predictive capabilities. Implemented advanced performance tuning techniques for Apache Spark, reducing query execution times and improving scalability. Established data governance frameworks, enforcing data privacy, data lin
  • AMN Healthcare
    Data Engineer
    AMN Healthcare
    Jun 2017 - Jul 2019 (2 years 2 months)
    Designed and optimized scalable ETL pipelines using Apache Beam, Python, and Google Cloud Dataflow, supporting high-volume data processing. Architected and implemented a data lake on Google Cloud Platform (GCP), enhancing data accessibility and cross-functional analytics. Developed and automated data quality validation frameworks using Great Expectations, reducing data discrepancies by 40. Standardized data models and schema designs to improve reporting consistency and reduce redundancy across business units. Integrated data from diverse sources, including REST APIs, flat files, and cloud databases, streamlining ingestion workflows and reducing delivery time by 30. Collaborated closely with analytics and engineering teams to support real-ti
  • C
    ETL & Data Warehouse Engineer
    Concertium
    Oct 2015 - May 2017 (1 year 8 months)
    Designed, developed, and maintained ETL pipelines using Talend, SSIS, and Apache NiFi, supporting cloud-based data warehousing solutions. Architected data warehouse solutions utilizing dimensional modeling, fact-dimension modeling, and Kimball methodologies, optimizing reporting performance. Implemented data quality automation frameworks, ensuring accuracy and consistency across enterprise systems. Developed real-time data integration solutions for healthcare and financial analytics using AWS and Google BigQuery. Created interactive dashboards and reports using Tableau, Power BI, and Matplotlib, enabling data-driven decision-making. Spearheaded cloud migration initiatives, ensuring smooth transitions from on-premises data systems to AWS, Az
Education verified_user 0% verified
  • Rice University
    Bachelor of Science, Computer Science
    Rice University
    Jan 2011 - Dec 2015 (5 years)
  • A
    AWS Certified Data Analytics – Specialty
  • G
    Google Professional Data Engineer Certification
    Kubernetes
Projects (professional or personal) verified_user 0% verified
  • F
    Financial Data Pipeline Modernization
    Developed scalable ETL pipelines with Apache Beam, Python, and Google Cloud Dataflow, processing over 10 million financial records daily. Designed a cloud-native data lake on GCP, enabling seamless access to structured and unstructured data for cross-team analytics. Implemented automated data validation and quality checks using Great Expectations, reducing data inconsistencies by 40.
  • C
    Cloud Data Lakehouse Migration
    Led the migration of legacy on-premises data infrastructure to a unified cloud-based lakehouse using Databricks and Delta Lake on Azure. Streamlined ETL workflows using Apache Spark and Talend, improving data refresh rates by 70. Integrated machine learning models with MLflow to forecast energy demands, increasing predictive accuracy by 30.
  • D
    Data Solution Architect
    Designed and led the development of a real-time healthcare analytics platform integrating EHR and claims data using Apache Kafka, Apache Flink, and AWS Kinesis. Enabled predictive insights for population health management and reduced data processing latency by 60. Deployed HIPAA-compliant data pipelines with Apache NiFi and Airflow on AWS, enhancing care quality and regulatory compliance.