Job Description

Key Responsibilities:

Leadership and Strategy

• Develop and implement the data engineering strategy aligned with the company’s business goals.
• Lead, mentor, and grow a high-performing data engineering team.
• Foster a culture of innovation, collaboration, and continuous improvement within the team.

Data Architecture and Infrastructure

• Design and oversee the implementation of robust, scalable, and efficient data architectures.
• Ensure the data infrastructure supports current and future data needs, including data warehousing, data processes, and big data technologies.
• Evaluate and implement new data technologies and tools to improve data processes and infrastructure.

Data Management

• Oversee the development and maintenance of data pipelines to ensure data quality and integrity.
• Implement best practices for data management, including data governance, data security, and data privacy.
• Ensure compliance with relevant data regulations and standards.

Collaboration and Communication

• Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver appropriate solutions.
• Communicate complex technical concepts and solutions to non-technical stakeholders effectively.
• Act as a liaison between the data engineering team and other departments, promoting data-driven decision-making.

Performance and Optimization

• Monitor and optimize the performance of data systems to ensure high availability and reliability.
• Develop metrics and KPIs to measure the effectiveness of data engineering initiatives.
• Identify and resolve performance bottlenecks in data processes and systems.

Project Management

• Lead data engineering projects from conception to completion, ensuring they are delivered on time and within budget.
• Manage project resources, timelines, and deliverables, coordinating with other teams as necessary.
• Ensure thorough documentation of data systems, processes, and projects.

Technical Skills:

• Proficiency in data engineering technologies and tools (e.g., Hadoop, Spark, Kafka, SQL, NoSQL databases).
• Experience with cloud platforms (e.g., preferable Google Cloud).
• Strong knowledge of ETL processes, data warehousing, and data architecture.
• Familiarity with data governance, data security, and compliance standards.
• Experience in big data technologies and real-time data processing.
• Knowledge of machine learning and AI principles and added advantage.
• Experience with data visualisation tools and techniques

Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field.
• Experience:
• Minimum of 15+ years of experience in data engineering or related roles.
• At least 5 years of experience in a leadership or managerial position.

EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.