Lead Data/AI Engineering

Job Description:

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

• Bachelors 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:

Time Type:

Location:

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.