Principal Data Engineer

Our prestigious client in Dubai Internet City is hiring principal data engineer.

Responsibilities:

1. Designing Data Architecture: Developing and architecting data systems and infrastructure to support the organizations data needs. This includes designing data pipelines data warehouses and data lakes.
2. Data Pipeline Development: Building and optimizing data pipelines for ingesting processing and transforming large volumes of data from various sources into usable formats for analysis and reporting.
3. Data Integration: Integrating disparate data sources and systems to ensure data consistency accuracy and reliability across the organization.
4. Performance Optimization: Optimizing data processing and query performance to ensure timely access to data for analytics and reporting purposes.
5. Data Governance and Security: Implementing data governance policies and procedures to ensure data quality integrity and security. This includes defining data access controls encryption and compliance with regulatory requirements.
6. Team Leadership: Providing technical leadership and guidance to a team of data engineers. This may involve mentoring junior team members conducting code reviews and driving best practices in data engineering.
7. Collaboration: Collaborating with crossfunctional teams including data scientists analysts and business stakeholders to understand data requirements and deliver solutions that meet business objectives.

Qualifications:

1. Strong Technical Skills: Proficiency in programming languages commonly used in data engineering such as Python Java or Scala. Experience with data processing frameworks like Apache Hadoop Apache Spark or Apache Flink is also essential.
2. Data Modeling and Database Skills: Expertise in relational and NoSQL databases as well as data modeling techniques. Experience with database technologies like PostgreSQL MySQL MongoDB or Cassandra is often required.
3. Big Data Technologies: Knowledge of big data technologies and platforms such as Apache Hadoop ecosystem (HDFS MapReduce Hive HBase) Apache Spark and cloudbased data platforms like AWS Azure or Google Cloud Platform.
4. ETL and Data Warehousing: Experience with Extract Transform Load (ETL) processes and tools as well as data warehousing concepts and methodologies. Familiarity with tools like Apache Airflow Talend or Informatica is beneficial.
5. ProblemSolving Skills: Strong analytical and problemsolving skills with the ability to troubleshoot complex data issues and devise effective solutions.
6. Communication and Leadership: Excellent communication and interpersonal skills with the ability to communicate technical concepts to nontechnical stakeholders. Experience leading and mentoring a team of data engineers is often required.

Remote Work :

No