Role Description We're looking for the right person to build that foundation from the ground up. This is a hands-on leadership role with real ownership: you'll shape how data is collected, structured, and delivered — and grow a team around you as the function matures. What You'll Be Working On - Design the target-state data architecture: Postgres CDC → Kafka → Snowflake → client-facing data products. - Own tooling decisions across ingestion, orchestration, transformation, and quality layers. - Implement CDC-based ingestion from PostgreSQL services (RDS, Aurora, EC2, K8s operator) using Debezium or equivalent. - Build streaming and near-real-time pipelines with defined SLAs. - Build a data quality control layer: checksums, reconciliation, schema validation, anomaly detection, and alerting. - Define quality checkpoints across the full pipeline — from source capture through Snowflake to client delivery. - Define and enforce data contracts with service-owning teams for core entities: transaction, merchant, settlement, and processing status. - Build the external data delivery layer: financial settlement, transaction status, processor reconciliation, and client analytics. - Design tenant separation and implement replay/reload mechanisms for failure recovery. - Start hands-on, then gradually hire and grow a small data engineering team as the function matures. - Build a pragmatic roadmap with concrete deliverables at 3, 6, and 12 months. Qualifications - 5+ years in data engineering with end-to-end ownership of production pipelines. - Hands-on with Snowflake, PostgreSQL CDC (Debezium preferred), and Kafka. - Solid AWS experience — S3, RDS, Aurora, and cloud data infrastructure. - Data quality engineering mindset: monitoring, reconciliation, lineage. - Comfortable defining data contracts and driving requirements with backend engineering teams. - Technical leadership experience: project ownership, cross-team alignment, delivery under constraints. - Kubernetes, Airflow/Prefect/Dagster, and dbt are strong pluses. - Payments domain knowledge — settlement, transaction lifecycle, processor integrations — is a strong plus. - Familiarity with gRPC, RabbitMQ, and reading Go/Python service code is expected. - English language skills at the B2 level and fluent Russian language. Benefits - An opportunity to make something great even greater, you can be the reason why we grow, develop, and become the best fintech company on the market! - Career prospects - we are young, we have huge ambitions, and it is important that our employees grow with us. - Work with coworkers who are passionate about their business. - Compensation that will fully correspond to the competence and knowledge, with yearly performance reviews. - Remote work. - 20 days of vacation time; bank holidays; sick leaves; additional birthday day off.

• Data Platform & Pipeline Engineering: Design and operate scalable, near real-time data pipelines for payment and platform data. • Financial Data Modeling: Model and process complex transactional and ledger-style data to support financial reconciliation, merchant reporting, and settlement tracking. • Data Quality & Observability: Ensure the accuracy and freshness of data across critical workflows. • Backend & API Development: Build and maintain backend services to expose data to internal platforms and downstream consumers. • Operational Ownership: Own systems end-to-end, from initial deployment to ongoing monitoring and reliability.

• Help guide projects within the team's area of ownership from ideation to delivery. • Turn normalized operational data into clean dimensional models (Kimball/star schema) that map to how commonsku works across orders, distributors, suppliers, products, and revenue. • Improve data trust and performance by optimizing queries, strengthening test coverage, and resolving pipeline reliability issues. • Define and protect canonical metric definitions in our dbt marts so every dashboard draws from a single source of truth. • Build accessible infrastructure in Snowflake and Metabase so analysts and business users can answer questions confidently, while diving into deep, hands-on analysis yourself when required. • Provide support, guidance, and constructive code reviews to our Data Engineer and Data Analyst. • Work closely with the Manager, Platform and Data, as well as Product Managers, to translate business goals into technical roadmap. • Integrate AI development tools like Cursor, CodeRabbit, and Snowflake Intelligence/Cortex to work efficiently, while proactively validating and refining their outputs.

Role Description This is an exciting opportunity for an experienced developer of large-scale data solutions. You will join a team delivering a transformative cloud hosted data platform for a key Version 1 customer. The ideal candidate will have a proven track record as a senior/self-starting data engineer in implementing data ingestion and transformation pipelines for large scale organisations. We are seeking someone with deep technical skills in a variety of technologies, Azure Data Factory, Azure Synapse Analytics, and SQL Server, to play an important role in developing and delivering early proofs of concept and production implementation. You will ideally have experience in building solutions using a variety of tools, and a proven track record in delivering high quality work to tight deadlines. Key Responsibilities - Design, develop, and maintain scalable data warehouse solutions Azure Synapse Analytics to support enterprise-level analytics and reporting needs. - Core responsibilities include building efficient Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) pipelines using Azure Data Factory conducting thorough data validation to ensure accuracy and consistency, and providing support for Business Intelligence (BI) reporting initiatives. - Strong proficiency in SQL is required for querying and data manipulation, along with experience in dimensional data modelling to optimize analytical performance. - Familiarity with reporting and visualization tools such as Power BI or Tableau is essential. - Developing scalable and re-usable frameworks for ingestion and transformation of large data sets. - Integrating the end-to-end data pipeline to take data from source systems to target data repositories ensuring the quality and consistency of data is maintained at all times. - Working with other members of the project team to support delivery of additional project components (Reporting tools, API interfaces, Search). - Evaluating the performance and applicability of multiple tools against customer requirements. - Working within an Agile delivery / DevOps methodology to deliver proof of concept and production implementation in iterative sprints. Qualifications - 3-5 years of experience in DWH implementation and should have Databricks experience. - Direct experience of building data pipelines using Azure. - Experience building data warehouse solutions using Azure Synapse Analytics. - Should have experience with Spark. - Candidates must possess hands-on experience with Structured Query Language (SQL), data quality management tools, and should be proficient in facilitating data exchange through Application Programming Interfaces (APIs). - Strong hands-on experience with SQL Server, advanced SQL query optimization, and relational database concepts. - Proficiency in the data concepts related to curation, archival, analysis, visualization and integrity. - Comprehensive understanding of data management best practices including demonstrated experience with data profiling, sourcing, and cleansing routines utilizing typical data quality functions involving standardization, transformation, rationalization, linking and matching. - Strong analytical, critical-thinking, and problem-solving skills. - Excellent communication skills and team-oriented approach. - Bachelor’s or master's degree in computer science, Business Information Systems, Mathematics, or related quantitative field. Desired Skills - Good knowledge in at least one business intelligence solution (e.g., Power BI). - Additional knowledge of data governance principles and metadata management practices is considered a valuable asset. Benefits - Share in our success with our Quarterly Performance-Related Profit Share Scheme, where employees collectively benefit from a share of our company's profits. - Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme. - Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance. - Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme. - Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. - Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies. - Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat. - Reward schemes including Version 1’s Annual Excellence Awards & ‘Call-Out’ platform. - Environment, Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes. - And many more exciting benefits… drop us a note to find out more.