Chief Data Architect

As a Director of Data Engineering, you will oversee the development and implementation of cloud-based data engineering solutions to support business analytics and reporting needs. This role involves managing a geographically diverse team responsible for ETL processing, transforming and deriving attributes from operational data for reporting and analytics use.

The ideal candidate will have a strong understanding of data warehousing concepts, including traditional and MPP database designs, star and snowflake schemas, and database migration experience. You should also have hands-on experience with ETL tools such as Pentaho, AWS Glue, Talend or Airflow, and knowledge of designing and implementing streaming pipelines using Apache Kafka, Apache Spark, Fivetran Segment.

Key Responsibilities:

• Manage a geographically diverse team of Managers/Senior Managers of Data Engineering responsible for the ETL to process, transform, and derive attributes for all operational data for reporting and analytics use from various transactional systems.
• Set and enforce BI standards and architecture. Align BI architecture with enterprise architecture.
• Partner with business leaders, technology leaders, and other stakeholders to champion the strategy, design, development, launch, and management of cloud data engineering related projects and initiatives that can scale and rapidly meet strategic and business objectives.
• Define cloud data engineering strategy, roadmap and strategic execution steps.
• Collaborate with business leadership and technology partners to leverage data to support and optimize efficiencies.
• Define, design & implement processes for data integration and data management on cloud data platforms, primarily AWS.
• Accountable for management of project prioritization, progress, and workload management across cloud data engineering staff to ensure on-time delivery.
• Review and manage ticketing queue to ensure timely assignment and progression of support tickets.
• Work directly with the IT Application Teams and other IT areas to understand, assess requirements and prioritize a backlog of cloud services needs to be delivered to enable transformation.
• Conduct comprehensive need assessments to create and implemented modernized server less data architecture plan that supports the businesses analytics and reporting needs.
• Establish IT Data & Analysis standards, practices and security measures to ensure effective and consistent information processing and consistent data quality/accessibility.
• Help architect cloud data engineering source to target auditing altering solution to ensure data quality.
• Responsible for data architecture, ETL, backup, and security of new AWS based data lake framework.
• Conducts data quality initiative to rid the system of old, unused, or duplicate data.
• Oversees complex data modeling and advanced project metadata development.
• Ensures that business rules are consistently applied across different user interfaces to limit the possibility of inconsistent results.
• Managed architected the migration of on premise DW SQL server star schema to Redshift.
• Designs specifications and standards for semantic layers and multidimensional models for complex BI projects, across all environments.
• Consults on training and usage for the business community by selecting appropriate BI tools, features, and techniques.

Required Skills and Qualifications:

• A People Leader with strong stakeholder management experience.
• Strong knowledge of Data Warehousing concepts with understanding of traditional and MPP database designs, star and snowflake schemas, database migration experience, with 4-5 Years of experience of data modeling.
• You must have at least 5 years of hands-on development experience using ETL Tools such as Pentaho, AWS Glue, Talend or Airflow.
• Knowledge on the architecture, design and implementation of MPP Databases such as Teradata, Snowflake or Redshift.
• 5 years of experience in development using Cloud-based analytics solutions preferrable (AWS).
• Knowledge of designing and implementing streaming pipelines using Apache Kafka, Apache Spark, Fivetran Segment.
• At least 5 years experience of using Python in a cloud based environment is definitely a plus.
• Knowledge on NoSQL DBs such as MongoDB is not required but preferred.
• Structured thinker and effective communicator.

Education / Certifications:

• Bachelors degree in Computer Science, Information Technology, or related fields (MBA or MS degree is a plus) or 15 to 20 years experience in lieu of a degree.