Salary by agreement
Experience from 5 years
A little about us: ggsel is a marketplace for digital goods. Since 2017, we've been at the top of CIS platforms. More than 6 million users choose us monthly for the best prices and quality support, and over the past year, we've grown 4 times. Our goal is not just to maintain our position but to revolutionize the digital goods market: make it honest, convenient, fast, and become a leader in digital commerce, including on the international market.
Currently, the product is undergoing a significant transformation, and we are assembling a strong engineering team. We already have professionals from Dodo, Yandex.Market, Samokat, and Avito.
We are looking for a Head of DWH to form the development strategy and manage data processing operations.
Tech stack: ClickHouse, SQL, Python, Airflow, dbt, PostgreSQL, Docker, Git.
Key Tasks
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DWH Strategy and Development
- Develop and defend a data warehouse development strategy for 1–3 years: scaling, migrations, new technology implementation.
- Define architectural standards and reference solutions for the data engineering team.
- Make decisions on technology selection and assess risks with a focus on data volume growth.
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Team Management
- Hiring, task assignment, deadline and quality control, performance reviews.
- Building development processes: code review, standards, documentation, knowledge sharing.
- Fostering a data-driven culture within the team and the company.
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Business Interaction
- Collect and prioritize requirements from business stakeholders, analysts, and Data Science.
- Agree on data contracts between source and data consumer teams.
- Present roadmaps and results to management, defend budgets and initiatives.
Requirements
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Deep knowledge of ClickHouse
- Schema Design: Architect-level expertise — selecting MergeTree engine families, partitioning and sorting keys, managing TTL for optimal compression and read speed.
- Query Optimization: Ability to read query plans, optimize memory consumption, configure materialized views and projections.
- Administration: Cluster planning, sharding and replication setup, merge monitoring, resource and storage cost management.
- Backup: Organizing backups to S3 and verifying recovery procedures (backup/restore, disaster recovery).
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ETL/ELT Tools and Orchestration
- Orchestration: Managing data collection via Apache Airflow (DAGs, sensors, retries, backfill).
- Transformation: Experience with dbt for building data layers (staging, marts, intermediate).
- Data Quality: Building a testing framework, monitoring data freshness and anomalies, data contracts.
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Languages and Infrastructure
- Python: Developing ETL scripts, working with Pandas, API integration.
- SQL: Expert-level proficiency (analytical queries, optimization).
- Infrastructure: Docker, Git, CI/CD, IaC (Terraform/Ansible), monitoring (Prometheus, Grafana).
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Management Competencies
- Team Management: Hiring, onboarding, development, performance review, engineer career paths.
- Planning: DWH roadmap, backlog prioritization, team OKRs, infrastructure budgeting.
- Stakeholder Management: Communication with C-level, product, analytics, security.
- Data Governance: Data catalog, lineage, ownership, compliance (GDPR/152-FZ), access control.
Conditions
- Remote work from anywhere in the world.
- Competitive salary + performance bonus twice a year.
- Flexible schedule and focus on results.
- Paid training, courses, and conferences.
- Opportunity to genuinely influence the product and the team.
Employment Type:
Full-time, Full working day, Remote
