Senior Data Engineer

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 742,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. We are uniquely able to deliver tangible outcomes because of our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song. These capabilities, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com

As a Data Engineer representing Accenture, you play a central role in elevating various facets of data operations, from optimizing data pipelines to ensuring the seamless flow of information. Your proactive problem-solving approach minimizes disruptions and guarantees the timely execution of data processes. Beyond operational excellence, you actively contribute to the enhancement of data products, collaborating closely with a diverse team of professionals to employ strategic methods for addressing data quality and elevating the overall user experience. Your expertise in data engineering, including proficiency in tools like BigQuery and workflows, contribute to the overall efficiency of the client's data operations, shaping their future through impactful insights and strategic contributions.

Responsibilities

• Analyze raw data to extract meaningful insights and patterns.

• Organize data in a structured manner for efficient utilization.

• Develop and maintain datasets to support various business functions.

• Ensure data integrity, accuracy, and availability.

• Implement strategies to enhance data quality and efficiency.

• Collaborate with cross-functional teams to identify and resolve data quality issues.

• Design, build, and maintain robust data systems and pipelines.

• Implement best practices for data architecture and integration.

• Combine raw information from diverse sources to create a unified dataset.

• Drive batch and streaming integrations between business applications and the data infrastructure.

• Employ ETL principles to streamline data integration processes.

• Optimize ETL workflows to ensure seamless data flow and accessibility.

• Design, build, and manage scalable and efficient data infrastructure on cloud.

• Ensure the security and performance of the data infrastructure.

• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.

• Collaborate with data governance teams to adhere to best practices and maintain data integrity

• Communicate effectively with team members to ensure alignment on data engineering objectives.

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