Senior Analytics Engineer, Current

• 6+ years of experience working as a data engineer or analytics engineer
• Implemented dimensional models and summarized data marts in the data warehouse; completed at least one full Data Warehouse development cycle
• Fluent in building data transformation pipelines, dimensional models and data marts. using one or more ETL or Transformation tools(Preferred: dbt)
• Proficient in dimensional modeling concepts to power meaningful analytics
• 3+ year of experience building meaningful metrics, reports and dashboards in BI/reporting tools like (Preferred: Looker)
• Strong expertise in SQL and performance tuning
• Experience working with services in cloud environment(s) like AWS or GCP
• Programing experience in Python, Scala or other language(s)
• Focus on data quality, integrity and security

Desirable

• This role on the data team will play an important part in contributing to the future of Current’s growth and serving data analytics and science needs of various teams at Current
• Building dimensional models in the data warehouse, data marts and transformation pipelines is something you are proficient at
• You will build Data Warehouse and Data Models at Current
• Partnering with data analysts, data scientists and engineers to support their data modeling and reporting needs will enable you to be successful in this role
• You will also work closely with the engineering team to build an efficient data infrastructure and tooling for data ingestion, transformation and analytics purposes
• Build data warehousing and data modeling strategy and roadmap
• Build core data models and data marts in the Data Warehouse
• Design and build data transformation pipelines, dimensional models, data marts and data aggregation layers in dbt, Airflow and Bigquery
• Implement scalable and easy to use data models housing complex data sets
• Support Looker as a primary data reporting and analytics tool and build core data models in Looker to easily do sophisticated data analysis
• Work closely with Banking, Product, Marketing, Finance, Credit, Risk and other teams to support their analytics and modeling needs in Looker
• Partner with data engineers to build data integrations, robust tools and infrastructure
• Implement framework and processes for data reconciliation and quality management
• Build trust and confidence in the data that you and your team will transform/produce