Job VC

We are looking for a
Senior Data/BI Engineer
to join a product-focused SaaS environment and help build a data-driven marketing platform. This is a great opportunity for someone with solid fundamentals who wants to grow beyond reporting into building data pipelines, shaping data models, and contributing to a scalable data ecosystem where data directly impacts product and strategy.
Responsibilities:
Design, build, and maintain dbt models — including incremental strategies, snapshots, schema design, macros, and lineage.
Design, build, and optimise ELT pipelines across ClickHouse, Snowflake, and PostgreSQL.
Lead and execute migrations from legacy systems (e.g., Snowflake dynamic tables) to dbt-based models.
Build validation frameworks comparing pipeline outputs across sources (e.g., legacy vs migrated models) to guarantee parity and correctness.
Build and monitor data orchestration with Apache Airflow.
Develop and maintain data collection pipelines from third-party REST APIs — authorisation, monitoring, retries, caching.
Data quality assurance: validation, error logging, observability, and consistency control.
Use Metabase as the primary BI tool for visualisations and quality monitoring dashboards.
Close collaboration with analytics, AI/ML, and client-side stakeholders to deliver clean, verified, and accessible datasets.
Requirements:
4+ years of experience as a Data Engineer or in a similar technical role.
Deep knowledge of SQL — complex queries, performance optimisation, warehouse-level thinking.
Deep knowledge of dbt for building data models, macros, and lineage.
Strong skills building pipelines with Airflow and a solid grasp of orchestration concepts.
Hands-on experience with at least one of: ClickHouse, Snowflake, or PostgreSQL (production-level, not just exposure).
3+ years of Python development experience, with a focus on data processing and API integration.
Experience with ELT (not ETL): data collection, processing, storage, and quality assurance.
Experience with BI tools — Metabase, Superset, Tableau, Quicksight, or similar.
Strong Git workflow: branching, PR reviews, conflict resolution.
Experience with CI/CD for data pipelines (GitHub Actions, Jenkins, or similar).
Comfort working with AI coding assistants (Claude Code, Cursor, Copilot) as part of daily workflow.
Nice to Have:
Hands-on experience tuning ClickHouse for analytical workloads.
Experience migrating from ETL to ELT architectures.
Practical experience with AWS (S3, IAM, CloudWatch).
Experience with AI-native data workflows or LLM-powered analytics use cases.
Understanding of data governance principles and data access control.
Our Benefits:
Professional growth
: Individual development plan, mentorship, reimbursement for professional certifications and English lessons, access to professional courses in the Corporate Learning Management System.
Community
: Tech community and knowledge-sharing events, English-speaking club, corporate library and book club, volunteering, and charity initiatives.
Wellbeing
: Medical insurance, regular medical check-ups, sport reimbursement, paid vacation and sick leave, mental health support, and events.
Work environment
: Fully-equipped offices, top-notch equipment, flexible work format, activities both in-office and online, Y-bucks, and access to the Yalantis store.
Please note that feedback on the results of the CV review will be provided only in the event of a decision to consider your candidacy further.
Otherwise, your data will be retained in the company’s CV database, and we will gladly contact you if a suitable vacancy becomes available. The consideration period is 7 working days.
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