• Develops specific marketing plans and activities for products and/or product lines to establish, enhance or distinguish product placement within the competitive arena • Provides thought leadership content and whitepapers that supports the positioning of the product • Contributes to the development and execution of a value proposition and messaging strategy for products in their portfolio • Converts the technical positioning of the product into key market messages, positioning collateral and sales tools prior to the launch of a new product • Articulates product propositions to clients and internal stakeholders, such as sales and consulting teams • Analyzes the competitive landscape and identifies the competitive differentiation of company product against competitor products • Drives market positioning programs and activities that are product-related, thereby clearly positioning the company and the product in the market • Creates client marketing/reference content such as datasheets, case studies, videos and references • Creates product presentation content that communicates the unique selling points, features and benefits of the product or solution • Works with internal teams to define and develop the required communication, training and other collateral that will enable the sales force to sell a particular product • Defines the content for and ensures the development of client collateral, sales tools, marketing programs, and sales programs • Influences the development of product go-to-market programs, initiatives and campaigns to drive awareness, interest and demand for the product • Tracks and monitors the success of the program on a scorecard or dashboard that reflects the associated metrics • Conducts product comparisons for new product initiatives and existing product enhancements and monitors product relevance in the context of changing market conditions and client dynamics

Role Description We are expanding our Data team and are in need of a rigorous Senior Analytics Engineer to partner closely with our Finance and Operations teams. This role will own the Finance/Operations data layer, bring new data into our warehouse from systems like NetSuite, Ramp, and Pigment, and build the dashboards and metrics leadership relies on to run the business. - Stakeholder Collaboration: Partner with Finance, Operations, and the rest of the Data team to understand business processes and source-system workflows, define pipeline requirements, and identify data gaps and downstream reporting impacts. - Data Infrastructure: Own the Finance and Operations data layer and build trusted, reusable data models that support reporting, analysis, and decision-making. - Data Integration: Design and document how data should flow between source systems such as NetSuite, Ramp, and Pigment into Snowflake and Omni. - Data Quality: Create validation checks, reconciliation workflows, and exception reporting to improve trust in critical Finance/Ops data across source systems, Snowflake, and Omni. - Metric Governance: Define and govern key Finance/Operations metrics with business owners, including business logic, data grain, source of truth, ownership, refresh cadence, and known limitations. - Dashboard Development: Create and maintain dashboards, from executive-level summaries to granular self-serve analytics, to communicate performance metrics and support root-cause analysis. - Continuous Improvement: Identify and execute opportunities to automate manual data flows, reporting processes, and reconciliation workflows. Qualifications - 5+ years in an analytics role with exposure to financial or operational data sets. - Strong SQL skills and experience building reusable, well-structured data models in a cloud data warehouse environment, ideally Snowflake. - Experience with BI or semantic-layer tools such as Omni, Looker, Tableau, Power BI, or Sigma. - Experience validating outputs, reconciling discrepancies, documenting assumptions, and creating checks for critical metrics. - Ability to understand business processes and translate them into data models, metrics, dashboards, and documentation. - Strong stakeholder management skills, including gathering requirements, managing expectations, pushing back constructively, and communicating tradeoffs. - Comfort working in an early-stage or evolving data environment where systems, pipelines, definitions, and ownership boundaries may still be forming. Requirements - Experience with source-of-truth systems such as ERP (NetSuite), WMS, TMS (OSCA), or CPM (Pigment). - Experience with wholesalers and EDI. Benefits - Competitive Salary + Equity Package - 401K matching - Wellness, learning, and home-office budgets - Health, Dental & Vision Medical Plans - Tremendous autonomy to set the direction of your work - Unlimited PTO - Company holidays on the first Friday of every month (Excluding November, December, and January)

• Data Modeling & Architecture: Design, build, and optimize modular dbt pipelines and performant technical schemas, setting the team standard for version control, unit testing, and velocity. • Cross-Functional Translation: Act as a critical technical bridge between Analytics, Operations, and Data Engineering to transform ambiguous product requirements into robust data assets. • Platform Optimization: Diagnose performance bottlenecks to slash query latencies and lower warehouse compute costs across our modern data platforms, specifically aiding our strategic migration toward Snowflake. • Team Stewardship: Elevate the entire pod’s engineering culture by participating in rigorous peer code reviews, refactoring legacy technical debt, and enforcing strict data security standards up to the point of delivery. • Culture Multiplier: Actively mentor and pair with junior peers to unblock complex bugs, optimize engineering workflows, and natively adopt AI-assisted development tools to accelerate test generation and legacy code discovery.

Role Description We are looking for an Analytics Engineer for our DWH. Our bank runs on data-driven processes, and the DWH team plays a central role in enabling that. We are responsible for building and maintaining data pipelines from all internal and external sources, developing data marts for reporting and analytics, and creating a toolchain that simplifies working with data across the company. In this role, you will partner directly with business stakeholders and act as a bridge between business and engineering. You will work deeply with risk data (risk engine, credit bureau, payments, risk indicators), building scalable, production-ready solutions on top of our DWH, while contributing to the development of the domain through data modeling, solution design, and close collaboration with business stakeholders. Challenges that await you: - Collaborating with Risk domain stakeholders to formalize and translate their data needs into structured ETL requirements - Decomposing risk-related domains (applications, rules, features, decision logic) into clear and maintainable data models - Analyzing potential data sources across raw and processed layers to identify optimal integration points - Designing logical data models and supporting the implementation of scalable ETL pipelines and data marts within the DWH - Defining and aligning key risk metrics (e.g. DPD buckets, default flags, aggregates) with business stakeholders - Coordinating and optimizing data flows between risk processes and core DWH components - Validating and iterating on data solutions together with business users - Ensuring data solutions are production-ready (scheduling, optimization, maintainability) - Contributing to the DWH knowledge base by documenting data lineage, transformations, and business rules - Promoting a strong data culture and proactively contributing to the development of the risk data domain Qualifications - 2-3 years of experience as a Data Analyst/Analytics Engineer or System Analyst DWH is required - Strong domain expertise in the Risk or Finance domain - Knowledge of data analysis techniques - Strong hands-on experience with SQL at the level of writing complex queries - Understanding of data modeling and data warehousing concepts - Open mind for problem-solving and good troubleshooting skills - Strong communication and collaboration skills to effectively work with cross-functional teams, including data engineers, analysts, and stakeholders, to deliver high-quality data solutions - Ability to work independently and as part of a team - Attention to detail and strong organizational skills - B1 or higher English level for effective communication with an international team Benefits - Relocation support to one of our hubs — Cyprus, Serbia, Georgia or Kazakhstan — with assistance for the employee and their family - Flexible work from one of our offices or remote - Healthcare Coverage - Education Budget: Language lessons, professional training and certifications - Wellness Budget: Mental health and fitness activity reimbursements - Vacation policy: 20 days of annual leave and paid sick leave