Works as an Individual contributor and key member of the Data and AI team and helps in timely execution of assigned deliverables with accurate estimates, work priorities, and accommodates project changes and trade-offs necessary for a successful release. Applies technical experience and industry-specific knowledge to develop solutions, based on an analysis of how the proposed approach affects the business objectives of customers and partners. Contributes to the overall efficacy and quality of a project team's technical delivery within assigned engagements. Defines dependencies and risks that go beyond the immediate scope and timeframe for a complex project. Develops contingency plans, risk-mitigation implementation criteria, and alternative strategies to manage short- and long-term risks and manages technical escalations. Align with innovation and digital transformation initiatives. Ensures the use of existing intellectual property (IP) and delivers value to customers. Responsible for implementing the technology strategy with support from Senior peers Applies information-compliance and assurance policies to ensure stakeholder confidence. Drives new ways of thinking, across the division and subsidiary, to improve quality, engineering productivity, and responsiveness to feedback and changing priorities. Consistently upskills through regular trainings and certifications on Azure Data and AI to be able to contribute to the future needs of the organization and customers 4 - 6 years of experience Bachelor's degree in computer science engineering or equivalent work experience. Higher relevant education is preferred. Knowledge of solution design, planning, development and deployment of complex solutions Hands-on experience in Data Engineering across cloud, on-prem, and hybrid environments Strong foundational experience with Azure Data Services and data platform modernization initiatives Experience/knowledge of one or more SQL and NoSQL database systems Hands-on experience building AI-powered data pipelines using ETL/ELT tools like: Azure Data Factory (ADF), SSIS, Talend, Informatica, Airflow Exposure to data migrations, platform upgrades, and modernization efforts Understanding of multitenant data platform designs, basic security hardening, and access control concepts Knowledge of Big Data ecosystems like Spark, Databricks, Kafka, Hadoop, etc. Experience building or supporting ML ready datasets and basic feature engineering Experience working in Agile teams with knowledge of/exposure to Azure DevOps Ability to work closely with senior consultants, architects, and customers to co-create innovative solutions with customers to help solve their business challenges Good understanding of core data architecture patterns: Dimensional modeling Lambda and Kappa architectures Timeseries data processing Familiarity with Azure Stream Analytics and Azure Analysis Services Awareness of data governance concepts and tools (opensource or proprietary)
