Sr Data Engineer

Responsibilities: • Collaborate with Sales & Marketing team members, data scientists, BI analysts, and other stakeholders to understand data needs and deliver solutions. • Develop the overall database/data warehouse structure based on functional and technical requirements. • Engineer physical and logical data models for dimensions and facts within the staging, warehouse, and semantic layers of enterprise data warehouses and platforms. • Performance tune SQL, Python, Incorta, or Informatica ETL pipelines, as well as Google BigQuery Dataprocs to move data from various source systems and file types into dimensional data models. • Utilize SQL within Google BigQuery, Informatica ETLs, Incorta pipelines, or Oracle SQL Views to achieve proper metric calculations or derive dimension attributes. • Engineer schedule and orchestration for batch and mini-batch data loads into enterprise data warehouses and platforms. • Provide issue resolution and maintenance for various business unit solutions existing in enterprise data warehouses and platforms. • Use tools such as SQL, Oracle Business Intelligence, Power BI, Tableau, Google Cloud Platform, Python, Incorta, and Informatica ETL to engineer data pipelines and models to enhance enterprise reporting and analytics. • Engineer dashboards within enterprise business intelligence platforms containing reports and visualizations with intelligent user interface design and flow for the business, ensuring adequate performance. Required Qualifications: • Bachelor's degree in Computer Science, MIS, or related area with experience in business intelligence, data engineering, and data modeling. • 4+ years of experience with reading and writing SQL. • 3+ years of experience engineering within a data warehouse or related experience with dimensional data modeling. • 3+ years of experience designing and developing ETLs/pipelines in Python, Google BigQuery Dataprocs and/or Informatica ETL. • 3+ years of experience with data enablement for a Point of Sale or Syndicated Consumption platforms. Preferably, Circana. • Ability to gather detailed technical requirements to design and develop data structures supporting business intelligence report solutions from beginning to end. • Excellent written and verbal communication skills. • Excellent organizational and time management skills. • Tested problem-solving and decision-making skills. • Strong pattern of initiative. • Strong interpersonal skills. • Applicants must not now, or at any time in the future, require employer sponsorship for a work visa. • Applicants must be authorized to work in the United States for any employer. Preferred Qualifications: • Advanced SQL reading and writing skills. • Experience developing data pipelines and queries within Google Cloud Platform (Google BigQuery) and/or Oracle Databases. • Experience engineering within a data warehouse or related experience with dimensional data modeling. • Experience tuning SQL and ETLs. • Proven ability to gather detailed technical requirements to design and develop business intelligence report solutions from beginning to end. • Experience with Sales/Marketing/Consumption data. • Experience with syndicated consumption providers or retailer-focused Point of Sale platforms. • Experience working within Google Cloud Platform with services like Dataflow, Datafusion, Pub/Sub, Cloud SQL, Cloud Storage. • Experience with Oracle SQL including advanced functions like analytical functions. • Experience tuning complex SQL and ETLs. • Experience within a core metadata model (RPD) including the physical, logical, and presentation layers for the enterprise business intelligence platform (OBIEE – Oracle Business Intelligence Enterprise Edition). Specific competencies include: • Data Structures and Models - Develops the overall database/data warehouse structure based on functional and technical requirements. Develops data collection frameworks for mainly structured and sometimes unstructured data. • Data Pipelines and ELT - Applies data extraction, loading and transformation techniques in order to connect medium to large data sets from a variety of sources. • Data Performance - With minimal guidance, troubleshoots and fixes for data performance issues that come with querying and combining medium to large volumes of data. Tests for scenarios affecting performance during initial development. • Visualizations and Dashboards - Designs and develops reports and dashboards that meet business needs. Leverages visualizations when possible to increase speed to identifying an insight.