Requirements
Minimum of 7 years of experience in data engineering within a corporate environment; Prior experience with databases (NoSQL or Relational databases). Data Engineering (Python, SQL) Any cloud platform (AWS, Azure, GCP) Modern Data Platforms (Snowflake, Databricks, DBT) Excellent communication skills with the ability to convey complex data concepts to non-technical stakeholders. Possess an analytical, proactive, and collaborative mindset.
Description
IntroductionA career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.Your Role And Responsibilities− Build and maintain the data architecture− Track and report key performance indicators (KPIs) and business targets in an accessible, business-centric language.− Develop and maintain business reports for all solutions, aligning them with business objectives and ensuring ease of understanding and consumption by business users.− Drive data-driven product optimization by identifying and suggesting improvements based on historical data analysis.Preferred EducationBachelor's DegreeRequired Technical And Professional Expertise− Minimum of 7 years of experience in data engineering within a corporate environment;− Prior experience with databases (NoSQL or Relational databases). Data Engineering (Python, SQL) Any cloud platform (AWS, Azure, GCP) Modern Data Platforms (Snowflake, Databricks, DBT) Excellent communication skills with the ability to convey complex data concepts to non-technical stakeholders. Possess an analytical, proactive, and collaborative mindset.KeywordsPreferred technical and professional experienceData Engineering, ETL, Data Pipelines , Data Warehouse, Data Lakes, Cloud Data Platforms, SQL, Python, Spark, Hadoop, Snowflake, DataBricks, DBT, Azure Data Factory, Synapse Analytics, Databricks, ADLS, Power BI, Azure SQL, Azure Functions, PySpark, ETL, Pipelines, Cloud Data Engineering, AWS Glue, Big Queries, AWS Glue, Amazon S3, Amazon Redshift.