Data Engineer

JOB SUMMARY

The Data Engineer is responsible for designing, developing, and maintaining scalable data solutions that support enterprise reporting, analytics, and operational needs across Global Technology Operations. This role builds and optimizes data pipelines, supports data warehousing initiatives, and contributes to the stability and performance of modern and legacy data platforms. The position partners with cross-functional teams to ensure reliable, secure, and high-quality data solutions aligned with business objectives. Through collaboration, innovation, and technical excellence, the Data Engineer helps enable data-driven decision-making across the organization.

RESPONSIBILITIES

• Design, develop, and maintain data pipelines and integration solutions that support enterprise analytics and operational reporting.
• Build and enhance data warehouse structures, data marts, and transformation processes to ensure scalable and reliable data delivery.
• Develop and maintain ELT/ETL workflows using approved enterprise tools and platforms.
• Collaborate with Product Owners, Business Analysts, and cross-functional technology teams to translate business requirements into technical solutions.
• Perform data validation, testing, and troubleshooting to ensure accuracy, performance, and data integrity.
• Support ongoing maintenance and optimization of legacy data integrations and applications as required by the supported vertical.
• Contribute to backlog refinement, sprint planning, and Agile ceremonies to ensure timely and effective delivery of assigned work.
• Follow established data governance, security, and quality standards to protect enterprise data assets.
• Document technical designs, data flows, and processes to ensure transparency and knowledge sharing across teams.
• Perform other job-related duties as assigned.

QUALIFICATIONS

DEGREE TYPE:

Bachelor's Degree

FIELD(S) OF STUDY:

Computer Science, Information Systems, Engineering, Mathematics or Related Field

EXPERIENCE

• Minimum of 3–5 years of experience developing and supporting data engineering, data warehousing, or cloud-based data solutions.
• Experience building and optimizing data pipelines and data transformation processes.
• Hands-on experience with SQL and at least one scripting or programming language such as Python.
• Experience working with relational and cloud-based data platforms (e.g., Snowflake, Oracle, SQL Server, or similar).
• Exposure to ELT/ETL tools (e.g., dbt, Matillion, or comparable technologies).
• Experience working within Agile delivery frameworks and tools such as Jira.
• Experience supporting enterprise-scale data environments.
• Exposure to AWS or other cloud platforms.
• Experience working in environments that support multiple business verticals.

COMPETENCIES & SKILLS

• Strong analytical and problem-solving skills with attention to data accuracy and quality.
• Ability to manage multiple priorities and meet deadlines in a fast-paced environment.
• Effective communication skills with the ability to explain technical concepts to non-technical stakeholders.
• Understanding of data modeling concepts and database design principles.
• Working knowledge of data governance and security best practices.
• Ability to collaborate effectively across cross-functional teams.
• Continuous learning mindset with interest in emerging data technologies and practices.