Data Engineer

Saal.ai; Abu Dhabi; On-site; AED 180,000 - 300,000; Full time

Job summary

Saal.ai in Abu Dhabi designs, builds, and operates scalable data platforms to enable analytics and decision-making. As a Data Engineer or Big Data Engineer, you will prototype, deliver, and run reliable data pipelines across batch and real-time use cases, collaborating with product, analytics, and engineering teams.

You will implement ingestion, storage, and data models, ensure observability, data quality, and governance, and work with technologies like NiFi, Kafka, Spark, Flink, Airflow, and

Qualifications

• Bachelor's degree required or preferred in CS/SE.
• 3-5 years in data engineering or big data roles.
• Experience with data ingestion, storage, and modeling.

Responsibilities

• Design and build scalable ingestion, storage, and management systems.
• Develop batch and streaming pipelines with NiFi, Kafka, Spark, Flink, Airflow.
• Implement data models and CDC for analytics and AI.
• Ensure pipelines are observable, tested, and compliant.
• Collaborate with product, analytics, and engineering teams.
• Protect data security and governance per policies.

Skills

Python

SQL

Scala/Java

Data modeling

Cloud data engineering

Apache NiFi

Kafka

Spark

Airflow

Education

Bachelor's degree in Computer Science or Software Engineering

Tools

Apache NiFi

Kafka

Spark

Flink

Airflow

Docker

Kubernetes

Debezium

MinIO/S3

Parquet

Job description

Designs, builds, and operates scalable, resilient data platforms that enable high-impact analytics, insights, and decision-making. Working with product, analytics, and engineering teams, the role rapidly prototypes, delivers, and runs reliable data pipelines and big data services in production

Key Responsibilities:

• Design and develop services for large-scale ingestion, storage, and management across RDBMS, NoSQL, logs, and event streams.
• Build and operate robust, scalable batch and streaming pipelines with Apache NiFi, Kafka, Spark, Flink, and Airflow.
• Develop highly concurrent, low-latency systems handling structured and unstructured data.
• Implement change data capture and data models (OLAP, dimensional, lakehouse) for analytics and AI.

Quality & Operations

• Ensure pipelines are deployable, observable, and operationally manageable, monitored against data SLAs.
• Implement data quality checks, lineage, documentation, and governance and access controls.
• Optimize the performance and cost of data storage and processing.
• Work with product teams and third-party providers on integrations, and with Data Scientists on datasets.
• Participate in sprint planning and delivery, and advise on emerging data technologies and best practices.
• Protect sensitive data (encryption, masking, least privilege) and comply with SAAL security and HSE policies.
• Data pipelines with Apache NiFi, Kafka, Spark, Flink, and Airflow (batch and real-time).
• Distributed data architectures, data modeling, OLAP design, and CDC (e.g., Debezium).
• Storage and messaging platforms (MinIO/S3, Kafka) and data formats (Avro, Parquet, ORC).
• Strong programming and scripting (Python, Scala, or Java) and advanced SQL.
• Agile delivery and Git version control. Excellent English; Arabic is an advantage.
• Enterprise analytics and reporting platforms; infrastructure and containerized deployments (Docker, Kubernetes).
• Lakehouse formats (Iceberg, Delta Lake), dbt, data quality tooling, and data preparation for GenAI (RAG).

Education:

• Bachelor's degree in Computer Science, Software Engineering, or a related field (preferred).

Certifications (preferred):

• Databricks, Confluent (Kafka), or cloud data engineering certifications are an advantage.

Experience:

• 3-5 years of professional experience as a Data Engineer or Big Data Engineer.