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Data Engineer

Overview

As a Data Engineer at Inception, you will be responsible for building and maintaining the infrastructure that supports data collection, processing, and storage. Reporting to the Lead Data Engineer or Principal Data Engineering, you will work closely with data scientists, analysts, and other stakeholders to ensure that data systems are reliable, scalable, and secure. Your work will be crucial in enabling data-driven decision-making across the organization.

 

The opportunity

The Data Engineer is a key technical role focused on developing and optimizing the company's data infrastructure. This role involves designing and implementing data pipelines, ensuring data quality, and collaborating with cross-functional teams to support various data initiatives. The ideal candidate will have strong technical skills in data engineering, experience with data architectures, and a passion for working with data.

 

Inception is the UAE’s national-scale enabler in AI Research and Development. Partnering with Microsoft's AI SaaS, we offer domain-specific Agentic AI Orchestrator platforms utilizing reasoning agents for precise and cost-effective services. Our focus includes AI incubation, IP creation, applied AI R&D, and AI investment products. By creating models tailored to specific domains and languages, we ensure superior accuracy and efficiency. Collaborating with top universities and industry giants to drive significant advancements in AI technology within the region.

 

Responsibilities

As a Data Engineer, you will be responsible for developing and maintaining data systems to support the company’s strategic goals. Your role will encompass a range of activities focused on data pipeline development, data quality, and cross-functional collaboration.

·       Data Pipeline Architecture and Development

o   Design, construct, install, test, and maintain highly scalable data pipelines with a focus on machine learning models and analytics.

·       Data Integration

o   Work closely with data scientists, ML engineers, and stakeholders to ensure that data is accessible, consistent, and reliable for ongoing projects.

·       API and Data Services

o   Develop and maintain APIs for data access and manipulation, and integrate with external data services as needed.

·       Data Storage

o   Manage and optimize data storage solutions for both structured and unstructured data, where structured data includes relational databases and unstructured data includes Text Image Audio and Video, Search Engines like Elasticsearch and NoSQL databases, to support the requirements of machine learning models.

o   Understand data engines and structure to effectively design solutions for transactional, analytics, and search purposes.

·       Data Quality and Governance

o   Implement processes to monitor data quality and ensure production data is always accurate and available for key stakeholders.

·       Collaboration and Support

o   Collaborate with ML engineers to assist in data-related technical issues and provide architectural guidance and solutions.

·       Security and Compliance

o   Ensure compliance with data security and privacy policies.

·       Documentation

o   Maintain clear and up-to-date documentation including data dictionaries, metadata, and architectural diagrams.

Qualifications

Skills and attributes for success

o   Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; or equivalent work experience.

o   3+ years of experience in a Data Engineering role.

o   Programming languages like Python, Java, and Scala and managing huge scale data potentially Terabyte to Petabyte.

o   Hands-on experience with big data technologies like Hadoop, Spark and Flink.

o   Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar.

o   Strong understanding of data warehousing concepts, ETL processes, and data modeling.

o   Experience with API development and integration with data services.

o   Experience with cloud platforms like Azure.

o   Knowledge in DevOps, CI/CD methods, and containerization technologies like Docker or Kubernetes.

o   Experience with real-time / streaming data processing.

Technical stack

o   Programming Languages: Python, Java, Scala, SQL, Bash

o   Big Data Technologies: Hadoop, Spark, Flink

o   Unstructured Data: Text, Image, Audio & Video

o   Databases: MySQL, PostgreSQL, MongoDB, Cassandra, HBase,  Redis

o   Cloud Platforms: Azure

o   API Development: RESTful APIs, GraphQL, OpenAPI

o   Data Services: Kafka, RabbitMQ

o   Containers: Docker, Kubernetes

 

What we look for

If you are a performance-driven, inquisitive mind with the agility to adapt to ambiguity, you will fit right in. You should be eager to explore opportunities to build meaningful collaborations with stakeholders and aspire to create unique customer-centric solutions. Bias for action and a passion to conquer new frontiers in the AI space is at the heart of the Inception community.

 

What working at Inception offers

Culture: An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations.

Career: Outstanding learning, development & growth opportunities via structured training programs and innovative, high-tech projects.

Work-Life: A hybrid work policy to strike the perfect balance between office and home.

Rewards: A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more.

 

If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.

 

 

Average salary estimate

$100000 / YEARLY (est.)
min
max
$80000K
$120000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Data Engineer, G42

At Inception, we're excited to invite a talented Data Engineer to join our innovative team in Abu Dhabi! As a Data Engineer, you’ll dive into the heart of our data infrastructure, crafting and maintaining the essential systems that enable seamless data collection, processing, and storage. Your expertise will directly impact our mission of leveraging AI technology, making your role pivotal to data-driven decision-making across the organization. You’ll collaborate closely with data scientists and analysts, ensuring our data systems are not just efficient but also reliable and secure. From designing robust data pipelines that integrate with machine learning models to implementing data quality governance, every day will present new challenges and opportunities to showcase your skills. You should have substantial experience in data engineering and familiarity with big data technologies like Hadoop and Spark. Proficiency in programming languages such as Python, Java, and SQL is crucial, as is an understanding of cloud platforms like Azure. At Inception, we pride ourselves on fostering a culture of growth, collaboration, and innovation. You will be part of an inclusive environment that encourages personal and professional development through structured training programs and exciting projects. If you’re ready to transform the AI landscape and thrive in a dynamic setting, Inception is the place for you!

Frequently Asked Questions (FAQs) for Data Engineer Role at G42
What are the main responsibilities of a Data Engineer at Inception?

As a Data Engineer at Inception, your primary responsibilities will include designing and maintaining scalable data pipelines, ensuring the integration of data systems to support various projects, and collaborating with data scientists and ML engineers to uphold data quality. Additionally, you'll manage both structured and unstructured data storage solutions and develop APIs for data accessibility.

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What qualifications are required for the Data Engineer position at Inception?

The ideal candidate for the Data Engineer position at Inception should hold a Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; or possess equivalent work experience. A minimum of 3 years of experience in data engineering and proficiency in programming languages such as Python, Java, and Scala are essential.

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What technology stack does a Data Engineer at Inception work with?

At Inception, Data Engineers leverage a variety of technologies, including big data tools like Hadoop, Spark, and Flink, as well as databases such as MySQL, PostgreSQL, and MongoDB. Familiarity with cloud platforms like Azure and experience in API development is also crucial for this role.

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How does the Data Engineer role support AI initiatives at Inception?

The Data Engineer role is integral to supporting AI initiatives at Inception by ensuring that high-quality data is available for machine learning models and analytics. This includes developing data pipelines and integrating external data services which help drive informed decision-making and enhance the effectiveness of our AI technologies.

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What is the work culture like for a Data Engineer at Inception?

Inception offers a vibrant work culture where collaboration, diversity, and innovation thrive. As a Data Engineer, you will enjoy a supportive environment that encourages personal growth, with opportunities for continuous learning and a hybrid work policy that promotes a healthy work-life balance.

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Common Interview Questions for Data Engineer
Can you describe your experience with data pipeline development?

In your response, focus on specific projects where you designed and implemented data pipelines. Highlight the tools you used, such as Hadoop or Spark, and emphasize your role in ensuring data quality and accessibility for analytics.

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How do you ensure the quality and reliability of data?

Discuss your strategies for monitoring data quality, such as implementing validation checks, maintaining documentation, and performing regular audits. It's vital to communicate your experience with data governance best practices.

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What big data technologies are you familiar with?

List the big data technologies you've worked with, such as Hadoop and Spark, and provide examples of projects where you applied these technologies. This shows your hands-on experience and comfort level with large data sets.

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Describe a challenging data problem you faced and how you solved it.

Think of a specific instance where you encountered data inconsistencies or storage issues. Explain the steps you took to diagnose the problem, the solution you implemented, and the outcome. This demonstrates problem-solving skills and resilience.

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What is your experience with cloud platforms, specifically Azure?

Share your familiarity with Azure services and any projects where you utilized this platform for data storage or processing. If applicable, mention specific tools such as Azure Data Lake or Azure SQL Database to showcase your expertise.

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How do you handle real-time data processing?

Discuss any experience you have with real-time data processing frameworks, such as Apache Kafka or Spark Structured Streaming. Highlight how you've integrated these technologies into your data engineering solutions.

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What programming languages are you proficient in and how have you applied them?

Outline your proficiency in programming languages like Python, Java, or Scala and provide examples of how you've used these languages to build data solutions or perform analysis in previous roles.

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Can you explain the ETL process and your role in it?

Describe the steps involved in the ETL (Extract, Transform, Load) process and how your contributions ensured the accuracy and reliability of the data throughout each stage. Reference tools and methodologies you utilized to optimize this process.

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How do you ensure data security and compliance?

Discuss your knowledge of data security best practices and regulations relevant to data management. Highlight any experiences you have in ensuring compliance with these guidelines within your previous roles.

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What is your approach to documenting your work?

Emphasize the importance of clear documentation in data engineering. Describe the types of documentation you maintain, such as data dictionaries and metadata, and how this benefits your team and stakeholders.

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G42 is a global leader in creating visionary artificial intelligence for a better tomorrow. Born in Abu Dhabi and with a global footprint, we champion AI as a powerful force for good. A tool to improve every aspect of life. A complement and enhan...

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Full-time, hybrid
DATE POSTED
March 29, 2025

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