• We are looking for a highly technical, hands-on Senior Data Engineer to drive the evolution of our data delivery platform while leading a team of data engineers. • This is a player-coach role: you will architect our next-generation data stack, build proofs-of-concept (POCs), and prove out new technologies before we commit to them at scale — and you will also manage and grow a team of engineers who report directly to you. • You will partner closely with engineering leadership to shape the technical direction of our pipelines while staying hands-on in the systems yourself • We are deliberately moving away from a locked-in, vendor-heavy stack toward a flexible, largely open-source architecture that keeps our options open. • We also expect our engineers to work in a modern, AI-assisted way — using AI coding tools and prompt-based workflows to move faster without compromising quality. • You should be energized by evaluating tools, building POCs, and making pragmatic, evidence-based decisions about what we adopt next. • This is a build-and-prove role — you are expected to write code, design schemas, profile queries, and get into the details to understand the "how" and "why" behind every pipeline, while also mentoring your team to do the same.

• You will design, build and maintain scalable, reliable data pipelines and data platforms supporting analytical and reporting solutions • You will work on end-to-end data engineering solutions – from data ingestion, through transformation and storage, to serving curated datasets for analytics and reporting • You will develop and optimize ETL / ELT pipelines using Databricks (Apache Spark, SQL, Python) and Delta Lake technologies • You will be responsible for data modelling, data structures and performance optimization in analytical data stores (lakehouse / data warehouse) • You will implement and maintain data quality, data validation and monitoring mechanisms ensuring accuracy, consistency and reliability of processed data • You will collaborate closely with data analysts, BI developers and business stakeholders to translate business and regulatory requirements into robust technical solutions • You will contribute to architecture decisions related to data platforms, data processing patterns and technology choices • You will support and mentor junior data engineers, helping them grow their technical and consulting competencies • You will actively participate in client-facing work – discussing requirements, presenting solutions and explaining technical concepts in an accessible way • In addition to project work, you will keep up with latest data engineering, cloud and Anti Financial Crime trends and contribute to internal initiatives and accelerators.

• Work in a high-paced operations environment of Salesforce, the largest SaaS platform on the planet, working on the delivery and operations of scalable and innovative solutions for our modular compute infrastructure and proactively defending and securing our customers' data • Conduct all day-to-day operations for the Data Center Installation of racks/enclosures and preparation of equipment to be installed • Update cable management system as changes are made to data center cable plant • Update asset management system as equipment is added and removed from the data center • Define tasks for each project and work with all Tech and Prod teams to meet project timelines as well as provide status to team members and management on the completion of all tasks • Provide all information to assist with Data Center capacity planning for space and power • Handle all vendor resources to complete tasks as defined in SOWs • Maintain relationship with providers to ensure day-to-day operational success • Research new Data Center infrastructure equipment advancements and recommend changes as needed • Conduct all audits as required by company policies • Coordinate with the onsite delivery and shipping of all equipment • Will be part of an on-call weekly rotation shared across the Las Vegas Engineering team

• Lead and provide expert support for data collection, data validation, data visualization, and analytics initiatives • Apply disciplined methodologies for the planning, analysis, design, and development of information systems on an enterprise-wide basis or across a business sector • Develop analytical techniques and methodologies to solve complex business and technical problems • Perform strategic systems planning, business information planning, and business analysis • Organize and analyze large volumes of structured and unstructured data sets using data analytical tools • Locate, access, merge, clean, and standardize data from multiple sources, and develop derived metrics • Create and implement data collection and analysis tools using programming languages such as Python, Databricks, SQL, Scala, R, and Java • Design, script, debug, and analyze data engineering solutions • Implement and create machine learning-based tools and processes • Apply distributed and parallel processing technologies (e.g., Spark) to handle big data analytics tasks involving large data volumes • Perform SQL Server data imports from CSV and TXT files • Leverage Excel and Google Suite for data analysis, reporting, and collaboration • Utilize supporting tools and platforms such as Pentaho (data import/transformation), Azure Data Studio, GitHub, and Smartsheet as needed • Document task requirements, work completed, processes, and technical details thoroughly • Communicate effectively with stakeholders across technical and business teams • Operate independently as a subject matter expert in a fast-paced, entrepreneurial environment