Senior Data Engineer
TypeFull-time job
LocationPoland
Posted3 hours ago
We is seeking a Senior Data Engineer to thoughtfully architect and build the foundation of our next-generation multi-tenant influencer marketing analytics platform. In this role, you’ll play a key part in shaping scalable, reliable data infrastructure that empowers our enterprise partners with accessible, meaningful analytics. You’ll work with modern analytical databases and BI platforms to help deliver clear, real-time insights at a significant scale.
This is a highly impactful and collaborative position where you’ll develop systems that gracefully process millions of social media posts, creator metrics, and campaign performance data—while upholding strong standards of data isolation, security, and trust for our enterprise clients. Your work will contribute to a supportive, dependable data ecosystem that enables teams and customers to thrive.
Location: Poland (Remote)
Working hours: 12 pm - 9 pm CET
Key Responsibilities
Build Scalable Data Infrastructure
Design and implement ETL pipelines migrating from transactional databases to analytical data warehouses
Create real-time data ingestion systems processing campaign data, user metrics, and business intelligence
Build multi-tenant data models with proper partitioning strategies for enterprise-scale clients
Develop data quality frameworks with comprehensive validation, monitoring, and alerting
Architect Multi-Tenant Security
Implement Row-Level Security (RLS) and Role-Based Access Control (RBAC) in analytical databases
Design dynamic permission models supporting organization-level and division-level data access
Build session-based context management for secure multi-tenant queries
Create comprehensive audit trails and access logging for compliance requirements
Optimize Performance at Scale
Design database schemas with advanced partitioning and indexing strategies
Build materialized views and aggregated tables for real-time analytics
Implement query optimization, data skipping, and compression techniques
Handle high-concurrency embedded dashboard usage with sub-second query performance
Integrate Analytics Platform
Build dashboard data sources with optimized SQL transformations
Handle complex data structures and parsing requirements
Create flat, denormalized tables optimized for embedded analytics consumption
Implement custom field handling for tenant-specific metadata requirements
Required Qualifications
5+ years of data engineering experience with production-scale systems
Expert-level SQL skills with analytical databases (columnar databases preferred)
Strong Python programming with data libraries: pandas, numpy, pyarrow
Experience with ETL orchestration tools: Apache Airflow, Prefect, dbt, or similar
Deep understanding of analytical databases, partitioning strategies, and OLAP optimization
Experience building SaaS data platforms with tenant isolation requirements
Knowledge of Row-Level Security (RLS) implementation in analytical databases
Understanding of RBAC patterns and session-based access control
Experience with authentication flows in data systems
Familiarity with compliance requirements (SOC2, GDPR) for multi-tenant data
Nice-to-Have Experience
Database Experience
Experience with columnar databases: ClickHouse, BigQuery, Redshift, Snowflake
Knowledge of streaming data platforms: Apache Kafka, Pulsar, Kinesis
Understanding of distributed systems and database replication
Analytics & BI Experience
Experience with embedded analytics platforms and dashboard frameworks
Knowledge of semantic modeling and metrics layers
Familiarity with data visualization and self-service analytics
Advanced Technical Skills
Experience with real-time data processing and event streaming
Knowledge of data mesh or data fabric architectures
Understanding of machine learning pipeline integration
Experience with data lineage and data catalog tools
Originally posted on Himalayas
This is a highly impactful and collaborative position where you’ll develop systems that gracefully process millions of social media posts, creator metrics, and campaign performance data—while upholding strong standards of data isolation, security, and trust for our enterprise clients. Your work will contribute to a supportive, dependable data ecosystem that enables teams and customers to thrive.
Location: Poland (Remote)
Working hours: 12 pm - 9 pm CET
Key Responsibilities
Build Scalable Data Infrastructure
Design and implement ETL pipelines migrating from transactional databases to analytical data warehouses
Create real-time data ingestion systems processing campaign data, user metrics, and business intelligence
Build multi-tenant data models with proper partitioning strategies for enterprise-scale clients
Develop data quality frameworks with comprehensive validation, monitoring, and alerting
Architect Multi-Tenant Security
Implement Row-Level Security (RLS) and Role-Based Access Control (RBAC) in analytical databases
Design dynamic permission models supporting organization-level and division-level data access
Build session-based context management for secure multi-tenant queries
Create comprehensive audit trails and access logging for compliance requirements
Optimize Performance at Scale
Design database schemas with advanced partitioning and indexing strategies
Build materialized views and aggregated tables for real-time analytics
Implement query optimization, data skipping, and compression techniques
Handle high-concurrency embedded dashboard usage with sub-second query performance
Integrate Analytics Platform
Build dashboard data sources with optimized SQL transformations
Handle complex data structures and parsing requirements
Create flat, denormalized tables optimized for embedded analytics consumption
Implement custom field handling for tenant-specific metadata requirements
Required Qualifications
5+ years of data engineering experience with production-scale systems
Expert-level SQL skills with analytical databases (columnar databases preferred)
Strong Python programming with data libraries: pandas, numpy, pyarrow
Experience with ETL orchestration tools: Apache Airflow, Prefect, dbt, or similar
Deep understanding of analytical databases, partitioning strategies, and OLAP optimization
Experience building SaaS data platforms with tenant isolation requirements
Knowledge of Row-Level Security (RLS) implementation in analytical databases
Understanding of RBAC patterns and session-based access control
Experience with authentication flows in data systems
Familiarity with compliance requirements (SOC2, GDPR) for multi-tenant data
Nice-to-Have Experience
Database Experience
Experience with columnar databases: ClickHouse, BigQuery, Redshift, Snowflake
Knowledge of streaming data platforms: Apache Kafka, Pulsar, Kinesis
Understanding of distributed systems and database replication
Analytics & BI Experience
Experience with embedded analytics platforms and dashboard frameworks
Knowledge of semantic modeling and metrics layers
Familiarity with data visualization and self-service analytics
Advanced Technical Skills
Experience with real-time data processing and event streaming
Knowledge of data mesh or data fabric architectures
Understanding of machine learning pipeline integration
Experience with data lineage and data catalog tools
Originally posted on Himalayas
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