Bir Ecosystem is seeking a highly motivated and experienced Data Engineers to join Data Technology team within Data Management Office. As Data Engineer you will lead and oversee the data engineering team to design, build, and maintain scalable data infrastructure. You will be responsible for ensuring the smooth ingestion, processing, and storage of large-scale data sets, facilitating robust data analysis, and supporting data-driven decision-making across the organization.

·      5+ years experience in data engineering

·      2+ years experience in production Spark Streaming

·      Deep understanding of Iceberg internals, lakehouse patterns, and large-scale analytics

·      Proven experience implementing SCDs in distributed systems

·      Strong Python & SQL, comfortable reading JVM-level Spark behavior

·      Experience running Spark on Kubernetes

·      Operational mindset: monitoring, alerting, incident response

·      Zero tolerance for fragile pipelines or undocumented logic

Nice to have:

• CDC systems (Debezium, Kafka-based ingestion)
• Performance tuning under cost and latency constraints
• On-prem or hybrid data platforms

Opportunities for professional growth and development

Competitive salary and bonuses

Comprehensive insurance coverage

Supportive work environment

Visa Premium salary card

Corporate discounts and events

Additional vacation days

Discounted education and employee loans

New cozy studio office in Port Baku Tower 2

Strong teamwork with Agile principles, regular team buildings and themed events

Multicultural environment with foreign colleagues sharing their best experiences

• Design, build, and operate Spark Structured Streaming pipelines (event-driven, CDC, API-based)
• Implement and maintain Slowly Changing Dimensions (Type 1/2) at scale
• Own data modeling and table design using Apache Iceberg (partitioning, compaction, schema evolution)
• Ensure pipeline reliability, SLAs, and data correctness across batch and streaming workloads
• Develop and operate Airflow-orchestrated data workflows
• Collaborate closely with Senior Data Engineers and DataOps on platform stability and performance
• Enforce data access controls, governance, and secure data sharing

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