• Design and deliver product data products on Databricks — owning ingestion, transformation, and serving layers across the medallion architecture (bronze/silver/gold) to produce certified datasets consumed across product, analytics, and the wider business • Lead the hard problems in the domain — event schema governance across multiple products, identity resolution and sessionisation, high-volume event pipelines, and modelling the path from product usage to engagement and learner outcomes • Define and evolve engineering standards — dbt patterns, event ingestion patterns, data contracts, testing, observability — and contribute to cross-cutting standards across the wider data function • Own data quality and contracts for the data products you ship — implementing quality checks, maintaining contracts as the interface between producers and consumers, and ensuring issues are caught early and remediated cleanly • Raise the technical bar around you — through code review, design input, pairing, and the kind of senior IC presence that lifts the engineers and analysts you work with • Translate operational complexity — multiple product event sources, schema drift, ongoing integration of acquired products — into clean, durable engineering execution the business can rely on

• Design and deliver enterprise data products on Databricks - owning ingestion, transformation, and serving layers across the medallion architecture (bronze/silver/gold) to produce certified datasets consumed across the business • Lead the hard problems in the domain - entity resolution, master data, integration of acquired systems, and the engineering complexity of operating across multiple ERP and CRM platforms • Define and evolve engineering standards - dbt patterns, ingestion patterns, data contracts, testing, observability - and contribute to cross-cutting standards across the wider data function • Own data quality and contracts for the data products you ship - implementing quality checks, maintaining contracts as the interface between producers and consumers, and ensuring issues are caught early and remediated cleanly • Raise the technical bar around you - through code review, design input, pairing, and the kind of senior IC presence that lifts the engineers and analysts you work with • Translate operational complexity - multi-system landscapes, ongoing integrations, fragmented source systems - into clean, durable engineering execution that the business can rely on

• Own and drive the design, development, and deployment of end-to-end data solutions and pipelines for enterprise clients. • Translate business requirements into technical data architectures, integration patterns, and models that align with phData methodologies, standards, and best practices. • Ensure solutions meet performance, security, reliability, and scalability requirements in production environments. • Ensure engagements are delivered on time, within scope, and with measurable business value for clients. • Collaborate with cross-functional partners including data engineering, software engineering, analytics, and platform teams to deliver successful client engagements. • Provide technical leadership during design and code reviews, proof-of-concepts, and implementation workshops. • Ensure high quality in deliverables through testing, documentation, and adherence to governance and change management processes. • Partner with practice and account leaders to identify opportunities to expand engagements, improve delivery, and standardize reusable patterns and components. • Contribute to internal initiatives such as developing accelerators, templates, playbooks, and best practices for cloud data platforms. • Create clear technical documentation, including architectures, roadmaps, and operational runbooks, that can be reused across engagements. • Share knowledge with peers through mentoring, informal coaching, and internal communities of practice. • Represent phData with professionalism in all interactions, communicating clearly with both technical and non-technical stakeholders.

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.