Senior Manager

Education & Experience

• 10 Years industry implementation experience with data integration such as BigQuery, Dataflow, Dataproc, Cloud Composer (Airflow), Datastream, Pub/Sub, Cloud Run, Cloud Functions, DBT, Apache Spark/PySpark, Hadoop ecosystem technologies, etc.3-5 years of management experience required
• 3-5 years consulting experience preferred
• Minimum of 5 years of data architecture, data modelling or similar experience
• Bachelor’s degree or equivalent experience, Master’s Degree Preferred 
• Strong data warehousing, OLTP systems, data integration and SDLC
• Strong experience in big data frameworks & working experience in Spark or Hadoop or Hive (incl. derivatives like pySpark (prefered), Spark Scala or Spark SQL) or Similar, along with experience in libraries / frameworks to accelerate code development
• Experience with major database platforms (BigQuery, SQL Server, Oracle, PostgreSQL, Hadoop, Snowflake, Redshift, Cloud Storage (GCS), etc.)
• Strong experience in orchestration & working experience in either Cloud Composer (Airflow), Cloud Workflows, Cloud Scheduler, Dataflow orchestration, or similar cloud orchestration technologies.
• Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.)
• Understanding of modern data warehouse capabilities and technologies such as BigQuery, real-time analytics, cloud-native ELT, CDC, lakehouse architectures, and Big Data.
• Understanding of on premises and cloud infrastructure architectures (primarily GCP, along with AWS and Azure).
• Strong experience in Agile Process (Scrum cadences, Roles, deliverables) & working experience in either JIRA, GitHub, GitHub Actions, Cloud Build, Terraform or similar with Experience in CI/CD using one or more code management platforms.
• 3-5 years’ development experience in decision support / business intelligence environments utilizing tools such as Looker, Power BI, Tableau, Qlik and BigQuery-based analytics platforms.

• Design, develop, test, and deploy data integration processes (batch or real-time) using tools such as BigQuery, Dataflow, Dataproc, Cloud Composer (Airflow), Datastream, Pub/Sub, Cloud Run, Cloud Functions, DBT, Cloud Storage (GCS), etc.
• Create functional & technical documentation – e.g. ETL architecture documentation, unit testing plans and results, data integration specifications, data testing plans, etc. 
• Provide a consultative approach with business users, asking questions to understand the business need and deriving the data flow, conceptual, logical, and physical data models based on those needs. Perform data analysis to validate data models and to confirm ability to meet business needs.
• May serve as project or DI lead, overseeing multiple consultants from various competencies
• Stays current with emerging and changing technologies to best recommend and implement beneficial technologies and approaches for Data Integration including BigQuery, Dataflow, Datastream, Dataplex, Vertex AI, Cloud Composer, and DBT.
• Ensures proper execution/creation of methodology, training, templates, resource plans and engagement review processes 
• Coach team members to ensure understanding on projects and tasks, providing effective feedback (critical and positive) and promoting growth opportunities when appropriate. 
• Coordinate and consult with the project manager, client business staff, client technical staff and project developers in data architecture best practices and anything else that is data related at the project or business unit levels
• Architect, design, develop and set direction for enterprise self-service analytic solutions, business intelligence reports, visualisations and best practice standards. Toolsets include but not limited to: SQL Server Analysis and Reporting Services, Big Query Looker, Microsoft Power BI, Tableau and Qlik.

Work with report team to identify, design and implement a reporting user experience that is consistent and intuitive across environments, across report methods, defines security and meets usability and scalability best practices

Graduate in Computer Science, Data Science, or related field. 6-8 years of experience in data engineering or related field.