Senior Lead Data Analytics Engineer

Senior Lead Data Analytics Engineer

Requirements

• Bachelor’s degree in a related discipline and 8 years’ experience in design and developing data engineering solutions.
• Cloud ETL and Analytics experience designing and building end to end production solutions/pipelines
• Exceptional programming skills and ability to utilize a variety of data/analytic tools (e.g., Spark, Tensorflow, Keras, SageMaker, Docker, Python.) and ability to master new languages quickly
• Experience in designing, developing, and maintaining data architectures that support business objectives, including data modeling, schema design, and ETL processes.
• Hands-on SQL experience is a must across on-prem, cloud database technologies
• Familiarity with DevOps practices, including CI/CD pipelines for data integration
• Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) and implementing data-driven AI capabilities.

Responsibilities

• Lead multiple projects in data integration, automation, and analytics to provide business insights for the network fulfillment operations team.
• Provide technical expertise in designing and developing AI/ML capabilities to enhance analytics and predictive modeling.
• Design and implement an architecture for efficient data storage, retrieval, and analysis, ensuring data quality and consistency.
• Lead ETL tool consolidation initiatives to build a network fulfillment data effectiveness layer.
• Design and develop ETL solutions in the cloud, leveraging data lake assets and automation solutions in Power Platform.
• Develop automated anomaly detection capabilities across multiple datasets/domains to reliably detect meaningful, actionable anomalies.
• Integrate data from various sources to create a comprehensive view of the organization’s business operations.
• Use basic and advanced analytics techniques to extract insights from data for data-driven decision-making.
• Develop and implement process metrics to measure the effectiveness and efficiency of processes.
• Collaborate with business leaders and stakeholders to provide insights for informed decision-making regarding business process effectiveness.
• Recommend process improvement initiatives based on data insights and work with cross-functional teams to identify optimization opportunities.
• Lead data engineers to maintain enterprise standards and best practices, ensuring compatibility, scalability, and integration with other data platforms.
• Ensure team members adhere to data integration and analytics practices within operational bounds consistently.

Preferred Qualifications

• Experience with data warehousing technologies such as Amazon Redshift or Snowflake is also desirable.
• Experience with big data technologies such as Hadoop, Spark, or Kafka is highly desirable.
• Experience with Tableau, PowerBI to support development activities within the organization
• Strong technical background to effectively understand data and processes within an organization to provide optimization recommendations
• Excellent data analysis skills and experience analyzing complex data sets to identify trends, patterns, insights that can be used to improve business processes.
• Strong leadership skills and the ability to lead teams providing technical solutions, building prototypes and enabling cross functional teams with the information/insights. Should be able to build relationships and collaborate effectively with stakeholders across the organization.
• Excellent communication skills, both written and verbal. The ability to communicate complex ideas and data analysis results to both technical and non-technical audiences is a must.

Benefits

No information provided on Benefits.