# Data Engineer (5+ years of experience) — ARRAY INNOVATION

Canonical: https://jobxdubai.com/jobs/li-4472727143-data-engineer-5-years-of-experience
Location: Manama, Bahrain
Type: full_time · Level: senior
Monthly salary: AED 24,350 to 48,700 per month (estimated, not employer-stated) (UAE salaries are tax-free)
Posted: 2026-09-28
Apply: https://www.linkedin.com/jobs/view/data-engineer-5%2B-years-of-experience-at-array-innovation-4472727143?_l=en

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## Description

COMPANY OVERVIEW

At ARRAY, we're not just another software services company—we're a team of dreamers, innovators, and trailblazers! From startup grit to big-tech aspirations, we're on a mission to redefine technology, put Bahrain on the global tech map, and grow into a powerhouse that inspires. If you're ready to be part of an exciting journey, we want you on our team!

KEY RESPONSIBILITIES

• Data Modelling: Design schemas and semantic layers (medallion bronze/silver/gold) that power AI-driven applications and analytics.

• ETL & Pipeline Architecture: Build and orchestrate ETL/ELT pipelines (batch and streaming) using Airflow and dbt, feeding cloud data warehouses and lakes.

• Lakehouse & Storage Architecture: Design and maintain data lake and lakehouse solutions using open table formats (Apache Iceberg, Delta Lake, or Hudi) over object storage, balancing cost, performance, and query flexibility.

• Database Engineering: Manage relational and NoSQL databases (PostgreSQL, MySQL, Oracle) supporting both transactional and analytical workloads, including performance tuning, replication, and migration between systems.

• Data Governance: Implement role-based access control, permission-aware retrieval, reconciliation, and data quality monitoring across data platforms.

• Cloud & Platform Integration: Deploy and operate data workloads on our Kubernetes-native platform (ArgoCD, Terraform) alongside core AWS services.

MUST-HAVE SKILLS

• Bachelor's degree in Computer Science or a STEM-based subject.

• 5+ years of experience in data or software engineering.

• Strong SQL and Python (or Java) skills.

• Hands-on experience building ETL/ELT pipelines using orchestration tools such as Airflow.

• Experience with cloud data warehouses and lakehouse architectures (e.g., Snowflake, Redshift, BigQuery, Apache Iceberg, or Delta Lake).

• Strong database fundamentals — schema design, indexing, query optimization — across relational (PostgreSQL, MySQL, Oracle) and NoSQL systems.

• Experience with unstructured data stores (Vector DBs, Document DBs) supporting AI/ML retrieval use cases.

• Working knowledge of containerized environments (Docker, Kubernetes) for deploying data workloads.

• CI/CD pipeline experience (GitHub Actions, GitLab CI, Jenkins, or similar).

• Working knowledge of Infrastructure as Code (Terraform or similar).

• Proficiency with version control (Git).

• Strong written and verbal English communication skills.

NICE-TO-HAVE SKILLS

• Apache Spark for large-scale batch and distributed data processing.

• Exposure to streaming/CDC tools (Kafka, Debezium, or Kinesis).

• Experience with data catalog and metadata management tools (Glue Data Catalog, DataHub, or Amundsen).

• Familiarity with Power BI dashboarding and reporting.

• AWS, Azure, or GCP certification.

• Experience migrating legacy on-prem databases to cloud-native platforms.

• Observability stack — Prometheus, Grafana.

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## Requirements

Bachelor's degree in Computer Science or a STEM-based subject. 5+ years of experience in data or software engineering. Strong SQL and Python (or Java) skills. Hands-on experience building ETL/ELT pipelines using orchestration tools such as Airflow. Experience with cloud data warehouses and lakehouse architectures (e.g., Snowflake, Redshift, BigQuery, Apache Iceberg, or Delta Lake). Strong database fundamentals — schema design, indexing, query optimization — across relational (PostgreSQL, MySQL, Oracle) and NoSQL systems. Experience with unstructured data stores (Vector DBs, Document DBs) supporting AI/ML retrieval use cases. Working knowledge of containerized environments (Docker, Kubernetes) for deploying data workloads. CI/CD pipeline experience (GitHub Actions, GitLab CI, Jenkins, or similar). Working knowledge of Infrastructure as Code (Terraform or similar). Proficiency with version control (Git). Strong written and verbal English communication skills.

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