Senior Data Warehouse, OLAP Engineer

This is a fully remote position, open to applicants in Armenia, +5 more countries.

📋 Description

• Design, develop, and sustain scalable OLAP and data warehouse solutions.

• Create and enhance data models for reporting, analytics, and extensive data processing.

• Construct fact tables, dimension tables, aggregation layers, and analytical datasets.

• Develop efficient ETL/ELT pipelines for processing and transforming substantial volumes of data.

• Write, analyze, and optimize intricate SQL queries.

• Review existing queries, schemas, and data-processing workflows, providing recommendations for performance enhancements.

• Identify bottlenecks related to data access, transformations, storage, and query execution.

• Design strategies for partitioning, indexing, distribution, sorting, and sharding.

• Ensure analytical workloads maintain performance as data volumes expand.

• Assess whether calculations should be performed in the database, processing layer, or pre-aggregated.

• Enhance data warehouse architecture, schema design, and storage efficiency.

• Build and maintain reusable data models and aggregation layers.

• Guarantee data quality, consistency, completeness, and traceability across analytical datasets.

• Monitor pipeline performance, query execution, and data warehouse resource usage.

• Troubleshoot production data issues and conduct root-cause analysis.

• Collaborate with backend engineers, data engineers, analysts, and product stakeholders.

• Document data models, transformation logic, dependencies, and architectural decisions.

⛳️ Requirements

• A minimum of 5 years of professional experience in data engineering, data warehousing, database engineering, or a related field.

• Strong practical experience with OLAP systems and data warehouse architecture.

• Extensive experience dealing with large and continuously expanding data volumes.

• Excellent command of SQL, including the ability to write and optimize complex analytical queries.

• Strong grasp of dimensional data modeling, particularly fact and dimension tables.

• Experience in designing star, snowflake, or other analytical schemas.

• Experience in developing and maintaining ETL/ELT pipelines.

• Strong understanding of query execution plans and database performance optimization.

• Familiarity with indexing, partitioning, sorting, data distribution, and sharding strategies.

• Experience with relational, column-oriented, or distributed analytical databases.

• Understanding of data aggregation, pre-calculation, incremental processing, and historical data management.

• Experience in identifying and resolving performance and scalability challenges.

• Experience maintaining data solutions on Linux platforms within cloud environments.

• Proven experience with technical troubleshooting and production support.

• Ability to work both independently and collaboratively with distributed teams across various time zones.

• Experience in Agile/Scrum development environments.

• Strong written and verbal communication skills in English.

• Plus: Experience with SingleStore/MemSQL or other distributed SQL databases.

• Plus: Experience with columnar or MPP analytical databases.

• Plus: Experience with AWS or another major cloud platform.

• Plus: Experience with data orchestration and transformation tools.

• Plus: Experience with streaming or near-real-time data pipelines.

• Plus: Experience with data lake or lakehouse architectures.

• Plus: Experience in building analytical solutions for SaaS products.

• Plus: Experience collaborating with data analytics, business intelligence, or data science teams.

• Plus: Experience with cybersecurity, vulnerability management, or vulnerability scanning technologies such as SCA, SAST, DAST, IAST, container scanning, or VM scanning.

• Plus: Understanding of security-related datasets, including assets, vulnerabilities, threats, findings, and risk scores.

🏝️ Benefits

• Comprehensive health insurance plans.

• Flexible working hours and remote work options.

• Opportunities for professional development and training.

• Access to cutting-edge technology and tools.

• Collaborative and inclusive work environment.