We are looking for a Software Engineer who will take ownership of the technical link between the core data platform and the semantic layer at our client — an international AdTech company headquartered in New York. The company builds analytics and verification software for digital advertising and evaluates every ad impression against four criteria: fraud prevention, brand safety, viewability and geo-location. The role’s mission is to make sure data reaches UIs, CLI tools and AI agents reliably and on time.

Responsibilities

Developing scalable solutions that extend application capabilities and improve data processing efficiency and system performance;
Leading the technical implementation between the core data platform and the semantic layer, ensuring reliable data delivery to downstream applications and workflows;
Designing data endpoints in the semantic layer that turn raw source data into structures usable by UIs, CLI tools and AI agents;
Establishing monitoring, data quality checks and operational best practices across pipelines for faster issue detection and resolution;
Taking full technical ownership of complex initiatives spanning data infrastructure and application/API components;
Working with product managers and the Data, Applications, Data Science and Customer Success teams to clarify requirements and ensure accurate, timely data delivery.

Requirements

7+ years of software development experience, including building and supporting production systems with a focus on reliability, scalability and performance;
Solid expertise in contract-based architecture, API design and building semantic and serving layers on top of data lakes or warehouses;
Hands-on experience with data lake / warehouse technologies: Parquet, DuckDB, S3-compatible object storage, lakehouse table formats (Iceberg), cloud warehouses (Snowflake);
Strong skills in at least one general-purpose language (Python or Go) and advanced SQL, with the ability to choose technologies based on project needs;
Experience with orchestration, containerization and Kubernetes;
Solid background in monitoring, observability and data quality practices;
Confident use of AI development tools (coding assistants, LLMs, agents) and interest in secure interfaces and contracts for AI-driven data access;
Ability to explain complex technical topics to non-technical stakeholders;
Proactive, self-driven and results-oriented mindset;
Availability for occasional meetings at 7–9 PM Kyiv time;
English at C1 level.

Nice to have

Experience with observability platforms (Prometheus, Grafana, OpenTelemetry) and data quality frameworks;
Knowledge of marketing analytics: multi-touch attribution (MTA), marketing mix modeling (MMM), experimentation or customer data platforms.

What we offer

Remote work with no location restrictions.
Flexible working schedule.
Paid vacation.
Paid sick leave.
Courses and professional training.

Send your CV!