THE WORK: As a Data Engineer specializing in Informatica Administration, you will work independently, become a subject matter expert, and actively contribute to innovative solutions for complex data challenges. Your expertise in Informatica Administration will be key as you engage in projects that drive data quality and governance. We value your contributions and the fresh perspectives you bring to our collaborative environment. Key Responsibilities - Design and develop reusable workflows for data ingestion, quality, transformation, and optimization. - Build scalable data pipelines for extraction, transformation, and loading (ETL). - Deploy data solutions into production environments with efficiency and reliability. - Migrate data from legacy data warehouses following cloud architecture principles. - Automate data flow processes to improve accessibility and usability for stakeholders. Mandatory Skills - Informatica – Intermediate - Data Governance – Intermediate - Data Quality Management – Intermediate - Data Strategy Design – Intermediate Nice-to-Have Skills - Data Compliance Policies – Beginner - Sensitive Data Handling – Beginner - Data Optimization Techniques – Beginner - Documentation of Data Processes – Beginner Bonus Points - Intermediate proficiency in data governance. - Advanced proficiency in data quality management. - Expert proficiency in cloud architecture. - Intermediate proficiency in data pipeline optimization. - Master proficiency in data compliance policies. About Accenture 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 791,000 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 www.accenture.com Declaración de igualdad de oportunidades en el empleo Creemos que nadie debe ser discriminado por sus diferencias. Todas las decisiones de empleo se tomarán sin importar la edad, raza, credo, color, religión, sexo, origen nacional, ascendencia, discapacidad, condición de veterano militar, orientación sexual, identidad o expresión de género, información genética, estado civil, ciudadanía ni ningún otro criterio protegido por la legislación aplicable. Nuestra rica diversidad nos hace más innovadores, competitivos y creativos, lo que nos ayuda a servir mejor a nuestros clientes y comunidades.

• Own a clearly defined data engineering product space, accountable for measurable customer and business outcomes • Partner closely with engineering and design to discover, shape, and deliver high-impact solutions • Translate strategy into outcome-focused roadmaps aligned to company and product goals • Apply strong product, design, and systems thinking to evaluate trade-offs across value, feasibility, and impact • Use qualitative insights, quantitative data, and experimentation to define success metrics and adapt direction • Guide execution through prioritization and hands-on collaboration from build through launch • Communicate progress, risks, and decisions with clarity, turning complexity into actionable insight • Continuously improve product practices and ways of working across teams • Leverage AI-enabled tools to enhance discovery, decision-making, and product outcomes

• Design, implement, and maintain the scalable data platform infrastructure (AWS, Kubernetes, EMR, Redshift, Glue, etc.) • Manage and evolve internal tools and frameworks for data ingestion and processing (e.g., Airbyte, Debezium, Airflow) • Build and maintain secure, automated CI/CD pipelines for platform components and infrastructure-as-code • Collaborate with DevOps and Security teams to ensure compliance, reliability, and scalability of the data platform • Support version control, release workflows, and automation for notebooks, jobs, and tools used by data producers and consumers • Ensure high availability and performance of core data infrastructure through observability and alerting integrations • Build and apply design patterns for data architecture • Build requirements with internal clients in structured tasks

• Design, implement, and maintain the scalable data platform infrastructure (AWS, Kubernetes, EMR, Redshift, Glue, etc.) • Data Modeling & Transformation: Design, develop, and maintain modular and scalable data models (using dbt and SQL) within our Redshift data warehouse to transform raw data into analytics-ready layers. • Manage and evolve client-faced tools and frameworks for data processing (e.g., QuickSight, Redshift Editor, Athena IDE, Metabase) • Build and maintain secure, automated CI/CD pipelines for data components and infrastructure-as-code. • Collaborate with DevOps and Security teams to ensure compliance, reliability, and scalability of the data platform. • Provide development environments, standardized workflows, and tooling (e.g., Sagemaker Studio, Athena IDE, Redshift Editor, etc.) to improve developer experience. • Support version control, release workflows, and automation for data transformation, jobs, data workloads and integrations used by data producers and consumers. • Ensure high availability and performance of data tools through observability and alerting integrations. • Implement data quality and validation checks (e.g., dbt tests, unit tests). • Contribute to maintaining data catalogs and documentation for lineage and governance. • Investigate and resolve issues in data pipelines, workloads, and integrations, ensuring SLAs are met. • Documentation of data flows, architectural setup and data model.