استخدام Data Engineering Team Lead

Requirements:

We are actively seeking an experienced and dynamic Data Engineering Team Lead to spearhead our data initiatives. The ideal candidate will possess a minimum of 10 years of comprehensive experience in data engineering, including a strong background in building robust data infrastructures and leading ETL processes. In addition to technical proficiency, we are looking for a strategic leader with a passion for fostering a culture of innovation, continuous improvement, and mentorship.


Responsibilities:

- Strategic Data Leadership: Take the helm in defining and executing the data engineering strategy. Provide direction for the team, leveraging deep technical knowledge and industry best practices.

- ETL Architecture and Implementation: Oversee the design, development, and maintenance of ETL processes, ensuring efficiency, reliability, and scalability. Implement best practices for data extraction, transformation, and loading.

- Big Data Expertise: Utilize extensive experience with big data technologies, including data lakes, distributed processing platforms, and streaming technologies. Proficiency in Spark and Kafka is essential.

- Machine Learning Integration: Collaborate with data scientists and analysts to integrate machine learning concepts into data engineering processes, focusing on feature engineering and supporting ML pipelines.

- Team Leadership and Mentorship: Lead and mentor a team of data engineers, fostering a collaborative and innovative culture. Provide guidance on technical challenges, and promote professional growth among team members.

- Communication and Collaboration: Effectively communicate data engineering strategies, risks, and progress to stakeholders, including the Head of Engineering, Chief Technology Officer, and the wider organization. Contribute to external communication through blog posts and newsletters.

- Business Intelligence Best Practices: Institute BI best practices such as dimensional modeling, ETL pipeline development, and large-scale distributed ETL pipelines to support machine learning initiatives.

- Continuous Improvement: Demonstrate a growth mindset by consistently seeking opportunities for process optimization, efficiency gains, and technological advancements. Encourage a culture of continuous learning and improvement within the team.

- Representation at Industry Events: Act as a representative of the organization by attending, presenting, and participating in conferences, meet-ups, and industry events.

 
Tech Stacks:

Your expertise should cover a comprehensive range of technologies including:

- Database Technologies: Proficiency in SQL Server.

  - Data Integration: Extensive experience with SQL Server Integration Services (SSIS).

- Business Intelligence: Mastery in SQL Server Reporting Services (SSRS), Power BI.

- Big Data Technologies: Proficiency in data lakes, distributed processing platforms, Spark, and Kafka.

- Data Modeling: Expertise in Power BI Desktop.

- Scripting Languages: T-SQL, Python.

- Data Warehousing: Proficiency in relevant technologies.

- Monitoring and Performance Tools: Implementation and utilization of tools for monitoring and optimizing data engineering performance, including "Mister Data."

- Collaboration Tools: Proficiency in collaboration tools and methodologies.


Qualifications:


- Minimum of 10 years of experience in data engineering.

 - Proven leadership experience with the ability to guide and inspire a team.

- Strong understanding of data engineering technologies.

- Excellent problem-solving and analytical skills.

- Experience in a high-volume FinTech business.

- Extensive experience with big data-related tools and techniques.

- Exposure to machine learning concepts.

- Proactive mindset with a bias for action.

- Growth mindset with a willingness to mentor and learn from others.

If you are a strategic and innovative Data Engineering Team Lead with a passion for building robust data infrastructures and leading ETL processes, we invite you to apply and play a pivotal role in shaping the future of our data initiatives!

Location: Attar Square 
Age: 25 TO 45