Senior Analytics Engineer

Responsibilities

• 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.

Requirements

• 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+ years of experience building meaningful metrics, reports and dashboards in BI/reporting tools like Looker (Preferred: Looker).
• Strong expertise in SQL and performance tuning.
• Experience working with services in cloud environment(s) like AWS or GCP.
• Programming experience in Python, Scala or other language(s).
• Focus on data quality, integrity and security.

Nice-to-Haves

• Experience modeling data in dbt and Looker.
• Experience working with Financial services companies.
• Experience working with one or more MPP databases (Preferred: Bigquery, etc.).
• Experience in D2C domains.