Lead Data Engineer

4 months ago


مصر, Egypt Qureos Inc Full time

**About Employer**:
Our mission is simple. We empower organisations to engage and communicate seamlessly with their customers. Since it was founded in 2006, Unifonic has consistently developed its product line and its markets to provide an affordable enterprise-grade multilingual, seamless omnichannel communications platform throughout the Middle East. Trusted by 5000+ of the world's most customer-centric companies. Unifonic combines your communications channels on one platform so you can streamline customer engagement.

***

**Job Title**: Lead Data Engineer

**Years of Experience**: 5+

**Location**: Egypt

**Salary Range**: To be determined

**Industries**: Technology

**Role Summary**:
As a Lead Data Engineer at Unifonic, you will be responsible for designing, developing, and maintaining data infrastructure and pipelines. You will collaborate with cross-functional teams to ensure data availability, reliability, and scalability. Additionally, you will optimize data systems and pipeline performance, implement data security and privacy measures, and troubleshoot data-related issues.

**Education**: Bachelor's degree in Computer Science, Data Science, or a related field (preferred)

**Qualification Summary**:

- Proven work experience with ETL Development or similar areas.
- Expertise in using containers and Kubernetes.
- Expertise in designing, deploying, and maintaining real-time stream processing pipelines.
- Expertise in using managed services provided by famous cloud providers like AWS, GCP, Azure (e.g., Managed DB, Object Storage, Managed K8s).
- Advanced knowledge in Database Engines, Data Lakes, Data Practices, and policies.
- In-depth understanding of database principles, data modeling, integration, ETL, ELT, data processing, and data management.
- Expertise in Data Warehouse & Data Lake technologies such as Vertica, Greenplum, Cloudera framework/ecosystems, Apache Kafka, Apache NiFi, Apache Spark, Impala, etc.
- Proficient in writing SQL and optimizing query performance.
- Experience assembling large, complex data sets that meet functional/non-functional business requirements.
- Experience building the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources and technologies.
- Experience working with private and sensitive information.
- Experience developing pipelines for ML (preferable).
- Superb communication skills.
- Analytical skills and strong organizational abilities.

**Responsibilities**:

- Design, develop, and maintain data infrastructure and pipelines.
- Collaborate with cross-functional teams to ensure data availability, reliability, and scalability.
- Optimize data systems and pipeline performance.
- Implement data security and privacy measures.
- Troubleshoot and resolve data-related issues.
- Stay up-to-date with the latest trends and technologies in data engineering.

**Skills Required**:

- Strong knowledge of data engineering principles and best practices.
- Proficiency in programming languages such as Python, Java, and Scala.
- Experience with ETL development or similar areas.
- Expertise in using containers and Kubernetes.
- Expertise in designing, deploying, and maintaining real-time stream processing pipelines.
- Expertise in using managed services provided by famous cloud providers like AWS, GCP, Azure (e.g., Managed DB, Object Storage, Managed K8s).
- Advanced knowledge in Database Engines, Data Lakes, Data Practices, and policies.
- In-depth understanding of database principles, data modeling, integration, ETL, ELT, data processing, and data management.
- Expertise in Data Warehouse & Data Lake technologies such as Vertica, Greenplum, Cloudera framework/ecosystems, Apache Kafka, Apache NiFi, Apache Spark, Impala, etc.
- Proficient in writing SQL and optimizing query performance.
- Experience assembling large, complex data sets that meet functional/non-functional business requirements.
- Experience building the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources and technologies.
- Experience working with private and sensitive information.
- Experience developing pipelines for ML (preferable).
- Superb communication skills.
- Analytical skills and strong organizational abilities.

Thank you for providing the information. If you need any further assistance, feel free to ask


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