Data Engineer

Gender; Muscat; On-site; OMR 18,000 - 32,000; Full time

Job summary

Gender is seeking an experienced Data Engineer in Muscat to design, develop, and maintain the data infrastructure for AI initiatives. You will build and manage pipelines that ingest, transform, and deliver data for analytics and decision making.

The role requires 6+ years in data management, strong expertise in Kafka, Airflow, Spark, and programming in Java or Python. You will collaborate across teams to ensure data quality, security, governance, and scalable, efficient data processing.

Qualifications

• Bachelor's degree in CS/DS/SE or related quantitative field.
• At least six years of experience in data management, integration, modeling, and data quality.
• Proven experience developing and maintaining data pipelines for AI projects.

Responsibilities

• Designs and develops data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems
• Collaborates with AI developers, data scientists and analysts to optimize models for data quality, security, and governance
• Integrates data from different sources, including databases, data warehouses, APIs, and external systems
• Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed
• Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques
• Optimizes data pipelines and data processing workflows for performance, scalability, and efficiency
• Monitors and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance
• Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data
• Supports the governance of data and algorithms used for analysis, analytical applications, and automated decision making

Skills

Problem solving

Cross-functional collaboration

Business acumen

Data governance awareness

Education

Bachelor's degree in CS/DS/SE

Master's degree preferred

Tools

Kafka

Airflow

Spark

Java

Python

C/C++

SQL

R

SAS

Excel

Snowflake

Databricks

AWS

GCP

Azure

Job description

The data engineer is responsible for designing, developing, and maintaining the infrastructure and systems required for data storage, processing, and analysis for AI initiatives. They play a crucial role in building and managing the data pipelines that enable efficient and reliable data integration, transformation, and delivery for all Al projects.

Key Responsibilities:

• Designs and develops data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems
• Collaborates with AI developers, data scientists and analysts to optimize models and algorithms for data quality, security, and governance
• Integrates data from different sources, including databases, data warehouses, APIs, and external systems
• Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed
• Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques
• Optimizes data pipelines and data processing workflows for performance, scalability, and efficiency
• Monitors and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance
• Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data
• Supports the governance of data and algorithms used for analysis, analytical applications, and automated decision making

Desired Candidate Profile

• A bachelor's degree in computer science, data science, software engineering, information systems, or related quantitative field; master's degree preferred
• At least six years of work experience in data management disciplines, including data integration, modeling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks
• Proven project experience developing and maintaining data pipelines for AI projects

Technical Skills:

• Expert knowledge in Apache technologies such as Kafka, Airflow, and Spark to build scalable and efficient data pipelines
• Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and Bl
• Strong ability in programming languages such as Java, Python, and C/C++
• Ability in data science languages/tools such as SQL, R, SAS, or Excel
• Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP) and modern data warehouse tools (Snowflake, Databricks)
• Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata
• Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products
• Expert problem-solving skills, including debugging skills, allowing the determination of sources of issues in unfamiliar code or systems, and the ability to recognize and solve repetitive problems
• Excellent business acumen and interpersonal skills; able to work across business lines at a senior level to influence and effect change to achieve common goals.
• Ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options
• Ability to translate among the languages used by executive, business, IT, and quant stakeholders.