Job Description

Your degree in Data Science, Data Engineering Computer Science, Information Technology or related as well as a minimum of 4 years proven experience in data engineering or related field will enable you to:Competencies & Skills:

• Strong technical expertise in data engineering concepts, tools, and technologies, with hands-on experience in data pipeline development, ETL, and data integration.
• Strategic thinker with a track record of driving business impact through data driven initiatives and solutions.
• Effective communication and stakeholder management skills, with the ability to influence and collaborate with senior leadership and cross-functional teams.
• Experience in defining and executing data strategies, roadmaps, and initiatives in alignment with business goals and objectives.
• Deep understanding of data governance, compliance, and regulatory requirements, with a focus on data security and privacy.

• Execute Data Strategy:

• Implement the company's data strategy, encompassing data architecture, governance, analytics, and data-driven decision-making.
• Define Best Practices and Standards:

• Implement best practices, standards, and methodologies for data engineering, ensuring adherence to industry standards and compliance requirements as defined by management.
• Establish guidelines for data acquisition, integration, storage, and analysis to ensure consistency, reliability, and scalability.
• Collaborate with Cross-Functional Teams:

• Collaborate with cross-functional teams to understand business needs and drive data-driven solutions that address specific challenges and opportunities.
• Partner with business leaders to identify opportunities for leveraging data assets and driving business value through analytics and insights.

• Evaluate Emerging Technologies:

• Evaluate and recommend emerging technologies, tools, and platforms to enhance data infrastructure, scalability, and performance.
• Stay abreast of industry trends and developments in data engineering and analytics and assess their potential impact on the organization's data strategy and capabilities.
• Establish External Partnerships:

• Establish and maintain relationships with external partners, vendors, and stakeholders to support data-related initiatives and partnerships.
• Collaborate with external partners to co-develop and integrate data related solutions that meet business needs and drive innovation.
• Drive Data Quality and Governance:

• Drive initiatives for data quality, governance, and security, ensuring data integrity, privacy, and compliance with regulatory requirements.
• Implement controls and safeguards to mitigate risks and protect sensitive information, maintaining the trust and confidence of customers, partners, and stakeholders.
• Lead Budgeting and Resource Allocation:

• Lead budgeting and resource allocation for data engineering projects and initiatives, ensuring alignment with strategic priorities and maximizing return on investment.
• Manage resources effectively to ensure timely delivery of data solutions and initiatives within budget constraints.
• Innovation in Data Analytics:

• Coordinate innovation in data analytics, machine learning, and artificial intelligence to unlock insights and drive business value.
• Champion experimentation and exploration of new tools, methodologies, and best practices to drive continuous improvement in data analytics capabilities.

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