Vice President - Core Engineering (Data Architect)

Qualifications:

• Experience: 14+ years of progressive experience in Data Engineering, Data Architecture, or related roles, with a strong focus on designing and implementing large-scale, enterprise-level data solutions.
• Education: Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a related quantitative field.
• Cloud Platforms: Expert-level proficiency and extensive hands-on experience with major cloud providers (e.g., AWS, GCP, Azure) and their data services (e.g., AWS S3, Redshift, Glue, EMR; GCP BigQuery, Dataflow, Dataproc; Azure Data Lake, Synapse, Databricks).
• Big Data Technologies: Deep expertise in big data technologies such as Apache Spark, Hadoop, Kafka, and distributed processing systems.
• Data Warehousing & Data Lakes: Proven experience with data warehousing (e.g., Snowflake, Redshift, BigQuery, Synapse Analytics) and data lake/lakehouse architectures (e.g., Delta Lake, Azure Data Lake Storage).
• Programming & Scripting: Strong programming skills in languages commonly used in data engineering (e.g., Python, Scala, Java, SQL).
• ETL/ELT & Data Integration: Extensive experience in designing, building, and optimizing complex ETL/ELT pipelines and data integration processes.
• Data Modeling: Mastery of various data modeling techniques (e.g., dimensional modeling, relational modeling) and tools.
• Databases: Strong understanding of various database technologies (SQL and NoSQL) and data platforms, especially in high-performance, high-availability contexts.
• Infrastructure as Code (IaC): Familiarity with IaC tools (e.g., Terraform, CloudFormation, Ansible) for managing data infrastructure.