Data Engineering Lead (advanced SQL & Python)

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 801,000 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. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, 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 accenture.com Role Description Serves as the primary point of coordination between the Client& Service Team. Works directly with the team to ensure on-time delivery of activities. Apply data engineering principles to develop reusable workflows including ingestion, quality, transformation, and optimization. Build scalable data pipelines using extract, transform and load tools. Deploy solutions to production environments. Migrate data from legacy data warehouses using cloud architecture principles. Automate the flow of data for consumption. The ideal candidate will have strong, hands-on experience managing data engineering initiatives and working closely with clients to understand their business needs. The role requires technical ownership, seniority, and depth in modern data engineering practices, beyond theoretical knowledge.

Design, build, and manage data infrastructure, growth marketing analytics conversion + expansion marketing, and product marketing reporting, etc. Lead the end-to-end design, development, deployment and optimization of critical data pipelines Architect ETL processes and ensure seamless integration of complex data sources Driving batch & streaming integrations between business applications and data infrastructure using ETL principles Expertly manage databases, optimizing performance and security Design advanced data models for complex analytical and reporting requirements Drive data quality initiatives and actively participate in establishing data governance standards Lead the deployment and management of data infrastructure on cloud platforms Develop sophisticated automation solutions and highly scalable data architectures Take a lead role and technical ownership in troubleshooting and resolving complex data-related problems in production environments. Mentor and provide technical guidance to junior and mid-level engineers Contribute to strategic decision-making and process improvements Required Experience Bachelor’s degree in computer science, Engineering, or a related field Proven experience as a Data Engineer or similar role Proficiency in programming languages like Python, C#(.NET Framework), Java, or Scala Experience with data integration tools and ETL frameworks (e.g., Apache NiFi, Talend, Informatica) Very High knowledge of SQL and database management systems (e.g., PostgreSQL, MySQL, MongoDB) Familiarity with cloud platforms and services (e.g., AWS, Azure, PLX, GCP) Knowledge of data modeling, data warehousing, and data architecture principles Understanding of data governance and data quality best practices Hands-on experience designing, building, and owning end-to-end data pipelines, including ingestion, transformation, testing, deployment, monitoring, and optimization. Experience with distributed data processing frameworks (e.g.,