Lead Data Engineer

ADA GLOBAL is looking for Lead Data Engineer to join our dynamic team and embark on a rewarding career journey

Responsibilities:

Data Architecture and Design:

• Lead the design and implementation of scalable data pipelines.
• Collaborate across teams to understand data requirements and propose innovative solutions.
• Evaluate and integrate cutting-edge technologies to enhance our data architecture.

Data Pipeline Development:

• Develop and maintain efficient ETL processes.
• Ensure data quality and integrity across the pipeline.
• Optimize existing data pipelines for performance improvements.

Team Leadership:

• Mentor and lead a team of skilled data engineers.
• Create a collaborative and innovative work environment.
• Align data engineering efforts with broader business objectives.

Data Governance and Security:

• Implement and enforce data governance policies.
• Ensure data security and compliance with regulations.

Spark Capabilities (Must-Have):

• Leverage Apache Spark for advanced data processing and analytics.
• Design and implement Spark-based solutions for large-scale data processing.

Monitoring and Maintenance:

• Establish and monitor key performance indicators for data pipelines.
• Troubleshoot and resolve data-related issues promptly.
• Implement proactive measures to prevent pipeline failures.

Qualifications:

1. Bachelor's or master's degree in computer science, Information Technology, or related field.
2. Proven experience as a Data Engineer (5-8 years).
3. Proficiency in SQL, Python, and other relevant programming languages.
4. Experience with data modelling, ETL development, and data warehousing.
5. Understanding of distributed computing and cloud platforms (e.g., AWS, Azure, GCP).
6. Leadership experience with a knack for inspiring and leading a team.
7. Strong problem-solving and communication skills.

Nice-to-Have:

1. Certification in relevant technologies (e.g., AWS Certified Big Data - Specialty).
2. Experience with big data technologies such as Hadoop or similar.
3. Knowledge of machine learning and data science concepts.