Lead Data/ai Engineering

This position requires frequent collaboration with developers architects data product owners and source system teams The ideal candidate is a versatile professional with deep expertise spanning data engineering software architecture data analysis visualization BI tools relational databases and data warehouse architecture across traditional and cloud environments Experience with emerging AI technologies including Generative AI is highly valued Key Roles and Responsibilities Lead the end-to-end design architecture development testing and deployment of scalable Data AI solutions across traditional data warehouses data lakes and cloud platforms such as Snowflake Azure AWS Databricks and Delta Lake Architect and build secure scalable software systems microservices and APIs leveraging best practices in software engineering automation version control and CI CD pipelines Develop optimize and maintain complex SQL queries Python scripts Unix Linux shell scripts and AI ML pipelines to transform analyze and operationalize data and AI models Incorporate GenAI technologies by evaluating deploying fine-tuning and integrating models to enhance data products and business insights Translate business requirements into robust data products including interactive dashboards and reports using Power BI Tableau or equivalent BI tools Implement rigorous testing strategies to ensure reliability performance and security throughout the software development lifecycle Lead and mentor engineering teams fostering collaboration knowledge sharing and upskilling in evolving technologies including GenAI Evaluate and select optimal technologies for platform scalability performance monitoring and cost optimization in both cloud and on-premise environments Partner cross-functionally with development operations AI research and business teams to ensure seamless delivery support and alignment to organizational goals Key Competencies Extensive leadership and strategic experience in full software development lifecycle and enterprise-scale data engineering projects Deep expertise in relational databases data marts data warehouses and advanced SQL programming Strong hands-on experience with ETL processes Python Unix Linux shell scripting data modeling and AI ML pipeline integration Proficiency with Unix Linux operating systems and scripting environments Advanced knowledge of cloud data platforms Azure AWS Snowflake Databricks Delta Lake Solid understanding and practical experience with Traditional Gen AI technologies including model development deployment and integration Familiarity with big data frameworks and streaming technologies such as Hadoop Spark and Kafka Experience with containerization and orchestration tools including Docker and Kubernetes Strong grasp of data governance metadata management and data security best practices Excellent analytical problem-solving and communication skills to articulate complex technical concepts and business impact Ability to independently lead initiatives while fostering a collaborative innovative team culture Desired knowledge of software engineering best practices and architectural design patterns Required Desired Skills RDBMS and Data Warehousing 12 years Required SQL Programming and ETL 12 years Required Unix Linux Shell Scripting 8 years Required Python or other programming languages 6 years Required Cloud Platforms Azure AWS Snowflake Databricks Delta Lake 5 years Required Power BI Tableau 5 years Desired Generative AI model development deployment integration 3 years Desired Big Data Technologies Hadoop Spark Kafka 3 years Desired Containerization and Orchestration Docker Kubernetes 2 years Desired Data Governance and Security 3 years Desired Software Engineering and Architecture 4 years Desired Education Experience Bachelor s degree BS BA in Computer Science Scientific Computing or a related field is desired Relevant certifications in data engineering cloud platforms or AI technologies may be required or preferred 13 years of related experience is the minimum however the ideal candidate will have extensive experience as outlined above DataEngineering Weekly Hours 40 Time Type Regular Location Bangalore Karnataka India It is the policy of AT T to provide equal employment opportunity EEO to all persons regardless of age color national origin citizenship status physical or mental disability race religion creed gender sex sexual orientation gender identity and or expression genetic information marital status status with regard to public assistance veteran status or any other characteristic protected by federal state or local law In addition AT T will provide reasonable accommodations for qualified individuals with disabilities AT T is a fair chance employer and does not initiate a background check until an offer is made