Notes:
This is NOT an entry level role, please review full requirements

WHO WE ARE
Here at FPG we believe in the potential of people. We transform front desk operations into profit centers for the leading hospitality brands worldwide by elevating the performance of their frontline agents, while enhancing guest satisfaction, through our proprietary software IN-Gauge.

WHO YOU ARE
You are an experienced data analyst with 3+ years of experience in ETL: Data pipelines, ETL concepts (DST), data-oriented cloud architecture, data warehousing, scalable technologies (such as column-store databases and Spark). Experience working in APIs, extraction methods, ETL and data warehouse environments. You have a mathematical approach to reviewing, analyzing and reconciliation of multiple data models and layers. You have the ability to critically problem solve, comprehend data veracity, reconciliation and processing challenges will be the primary objective of the role.

WHAT YOU WILL DO
With the world becoming increasingly intelligent and a continuous shift to the cloud, data is an essential source of understanding and insight. It’s however, not enough to have the data. It needs to be reliable, accurate. We gather, ingest and reconcile vast layers of unstructured, limited veracity on multiple data pipelines every day. Our dataset is continuously growing as we continue to add new customers into our Portfolio and will require an adverse and flexible approach to document new processes. This role validates the customer and processed layer of data while also working closely with our data architecture team. You will support FPG customers and internal engineering teams. HOW YOU WILL DO IT

• Resolve and support cross-functional teams to reconcile issues supporting implementation and large deployment challenges.
• You will be expected to (get your hands dirty) be involved supporting customer facing calls and execute the ING technical framework. You will need to be flexible when required to support other time zones.
• Assist in the documentation and support of our internal data council consisting of data reconciliation frameworks and processes that are effective, repeatable and scalable
• Consolidate and mange master data from on-premises and cloud data sources.
  • Support the architecture and ETL teams to construct data integration pipelines.
  • Validation of raw and processed data
  • Anomaly detection while support DQ rules
  • Automatically detect changes to DQ rules and improve quality over time
  • Provide data quality recommendations and pipelines to customers
  • Manage customer and DR profiles of customers
• Support and work closely with our architecture team on data lineage recommendations
• You will be an expert in verbal and written communication
• You will have the ability to strategically present complex data challenges and collaborate to engineer scalable solutions
• Works with minimal direction from the technical lead and with customer nominated representatives to accomplish assigned tasks.
• Contributes to design for specific data deliverables and assists in the development of customer data solutions.
• Participates as part of a team and maintains good relationships with team members and customers.
• Communicate findings to management and our partners effectively, using sound analysis, presentation, and business judgement

DESIRED SKILLS AND EXPERIENCE Technical Skills

• Experience working in APIs, extraction methods, ETL and data warehouse environments
• AWS S3, Redshift, Kafka, Glue
• SQL, AWS Quick-sights and other Data visualization tools
• Leverage domain expertise and data
• Knowledge of PMS/RES applications a strong advantage (property management & reservations)
  • Opera Cloud, On Prem, All Brand PMS apps,
• Knowledge of data extraction methods, batch, data lake or warehouse extraction methods, data
  • mapping, API methods and gateway, RESTful/GraphQL APIs

Requirements 3+ years in ETL: Data pipelines, ETL concepts and frameworks (DST), data-oriented cloud architecture, data warehousing, scalable technologies (such as column-store databases and Spark) 3+ years in experience specifically in “data analyst” or data science roles