Data Engineer Specialist job opportunity at Accenture Plc.

Bachelor's (B.Sc.)

San Jose, Costa Rica

San Jose....Costa Rica

summarize with Ai

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 accenture.com. We’re seeking a hands-on Data Engineer to design, build, and optimize secure, high-performance data pipelines and storage solutions. You will work with modern data platforms (Snowflake, Databricks, Denodo) and industry-standard tools (Hadoop, Spark, Airflow) using core languages (SQL, Python, Scala) to deliver reliable ETL/ELT processes, robust data models, and efficient database architectures. Your work will enable scalable analytics and data-driven decision-making across the organization. Key Responsibilities Data Processing & ETL Pipelines Design, develop, and optimize ETL/ELT pipelines for batch and streaming data using SQL, Python, Scala, Apache Spark, and Hadoop. Implement data ingestion, transformation, and loading processes from diverse sources into centralized data stores. Build reusable components for data movement, cleansing, and enrichment. Ensure data quality through automated checks, reconciliation, and regression testing. Data Storage & Databases Model and maintain relational and analytical databases (Snowflake, Databricks, Hadoop/HDFS, etc.), including schema design, partitioning, and indexing for performance. Manage data storage solutions, including cloud data warehouses, lakehouses, and Hadoop clusters. Optimize database queries and storage strategies for scalability and cost efficiency. Implement security, governance, and access controls for data assets. Pipeline Orchestration & Reliability Orchestrate data workflows using Airflow and dbt, as well as Databricks notebooks. Monitor and tune pipeline performance, reliability, and cost. Automate deployment and CI/CD for data pipelines and database changes. Collaboration & Documentation Work closely with analytics, product, and platform teams to understand data requirements and deliver scalable solutions. Document data flows, pipeline architectures, and database models for transparency and maintainability. #LI-LATAM