Software Engineer (Data Platform)
Summary
Software engineer owning the technical bridge between a core data platform and its semantic layer at a New York-based AdTech client, ensuring data reaches UIs, CLIs and AI agents reliably. Day to day: designing data endpoints/APIs, building on data-lake tech (Parquet, DuckDB, Iceberg, Snowflake), and monitoring pipelines using Python or Go, SQL and Kubernetes.
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!