Eldorado.gg is a leading marketplace for in-game items, accounts, and services, founded in 2018. Built by a team of 160+ professionals who care about speed, security and user experience. We support 150+ games such as Roblox, League of Legends and Fortnite, attracting more than 7 million monthly visits and reaching a global audience every day. We value bold ideas, move fast and continuously push the boundaries of digital trading. Join us and be part of a team where your work makes a real impact!

We’re growing and looking for our first dedicated Senior Data Engineer to join a newly formed team focused on search, discovery, and rankings across our marketplace.

Up until now, our data stack has been built and operated mainly for analytics - dashboards, reporting, and ad-hoc analysis. This role marks the shift to production-facing data infrastructure: pipelines whose output feeds product features and directly affects what users see on the marketplace. Reliability, freshness, and schema stability stop being conveniences and become product concerns.

👉 POSITION BREAKDOWN

• Set the technical direction for our production data engineering work - proposing the architecture, choosing the tools, and owning the implementation roadmap;

• Audit our current ingestion paths (Airbyte, Stitch) with a production-serving lens - what's good enough for a dashboard isn't good enough for ranking - and stabilize SQL Server → BigQuery flows for ranking-relevant tables;

• Establish automated testing, deployment, and code-review practices for data pipelines, and formalize a production feature-table layer in dbt that's distinct from the analytics models;

• Build clean, versioned, production-grade feature tables in partnership with our Data Scientist;

• Set up orchestration (Airflow / Dagster) with alerting, backfills, and failure handling appropriate for production dependencies;

• Instrument behavioral events (impressions, clicks, conversions) end-to-end as a pipeline deliverable, and coordinate with backend engineers on event schemas and data contracts;

• Introduce data quality checks, monitoring, and freshness/reliability targets so the Data Scientist has trustworthy training data and the serving path has trustworthy features;

• Close freshness gaps on time-sensitive signals, optimize BigQuery cost and performance, and grow our governance and schema discipline as the team scales;

• As the data science work matures, lay the foundations for ML-grade training data - point-in-time correctness, training/serving consistency - so models can be trusted in production.

👉 WHAT MAKES YOU A GREAT FIT

• Proven hands-on data engineering experience, including end-to-end ownership of production pipelines (not just scripts on a schedule);

• Production experience on a cloud data warehouse (BigQuery preferred, Snowflake or Redshift transferable);

• Experience reliably extracting data from production transactional databases - ideally SQL Server - in ways that preserve change history and support downstream correctness guarantees;

• Strong SQL skills and experience designing analytical data models that other people build on;

• Strong Python or scripting skills for production pipelines;

• Orchestration tooling experience - Airflow, Dagster, Prefect, or equivalent;

• Version control, automated testing, and continuous deployment applied to data systems - you treat data code like production code;

• Comfortable auditing and stabilizing inherited, partially-broken pipelines, not just greenfield builds;

• Pragmatism about tradeoffs between scale, maintainability, and cost - you avoid over-engineering.

👉 BONUS POINTS

• Hands-on experience with dbt or a similar transformation layer in production;

• Event instrumentation and schema design experience - you treat events as long-lived contracts;

• Experience with data quality and observability tooling (Great Expectations, Monte Carlo, Soda);

• Azure ecosystem experience (Data Factory, Event Hubs, Blob Storage);

• Streaming experience (Kafka, Pub/Sub, Dataflow, Debezium);

• Understanding of Infrastructure as Code (Terraform, Pulumi);

• Feature store or other machine-learning-adjacent data work;

• Background working with search, recommendations, or marketplaces.

👉 OUR DATA STACK

Our stack today is mainly analytics-leaning, and you'll help evolve it to also serve production features reliably:

• MS SQL Server as the production transactional source;

• Airbyte (with custom connectors) and Stitch for ingestion;

• Google BigQuery for storage and warehousing;

• dbt for data modeling and transformation;

• Cube as the analytics semantic layer;

• Amplitude for product analytics, Grafana for visualization, GrowthBook for A/B testing;

• Serving paths today include direct database reads and Azure AI Search for some ranking surfaces; Redis is in use elsewhere in the product, and we see it as a likely candidate for low-latency feature serving in future ranking work.
  

👉 PERKS & BENEFITS

• Growth opportunities: Access to an internal library, latest tools and technologies, professional conferences, and mentorship to level up your skills, opportunities for internal career growth;

• Health & wellbeing: Private health insurance after the probation period, additional sick days (no doctor’s note needed), and the option to join free volleyball games at Delfi Arena with colleagues;

• Office perks: Free parking, a fully stocked kitchen, Friday bun breakfasts, and a gaming room (table football, driving simulator, PS5, Xbox One); we’re pet-friendly and love team activities from game nights to sports events;

• Additional time off: Extra vacation days added annually (+1 day per year), with a cap of up to 10 additional days;

• Equity opportunities: Top-performing employees have the opportunity to be included in the generous company’s stock options program;

• Extra perks: Monthly top-ups for your Eldorado.gg account after probation, gifts for important life events, partner discounts, and referral bonuses;

• Hybrid work model: Built around an office-first mindset - 4 days in-office (Simbiocity, Vilnius) and 1 day remote.

👉 GROSS SALARY

The salary range for this position is 5000-8500 eur gross per month, depending on your experience.

👉 WHAT TO EXPECT NEXT

Shortlisted candidates will be contacted by our Talent Acquisition team and invited to complete the following stages: HR interview, test task, and hiring manager interview.