Senior Lead Data Analytics Engineer

Company

Cox Communications, Inc.

Job Family Group

Engineering / Product Development

Job Profile

Sr Lead Data Engineer

Management Level

Sr Manager - Non People Leader

Flexible Work Option

Hybrid - Ability to work remotely part of the week

Travel %

No

Work Shift

Day

Compensation

Compensation includes a base salary of $131,600.00 - $219,400.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate’s knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.

Job Description

We are seeking a highly skilled experienced Senior Lead Data Analytics Engineer responsible for designing, developing and maintaining the data integration and analytics solutions to support initiatives under network operations data effectiveness organization. A proven track record in the Data Integration and Analytics ecosystem with experience in working with leadership teams on developing long term strategies that provide value to the business. To be successful in this role one must be able to work effectively in a high volume, extremely fluid and fast-paced data environments with experience working across latest technologies along with the understanding around data across systems. Senior Lead will balance hands-on technical expertise with thought leadership to deliver scalable, secure, and innovative solutions that meet organization goals

Key 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.

Qualifications 

Minimum:  

• Bachelor’s degree in a related discipline and 8 years’ experience in design and developing data engineering solutions.
• The right candidate could also have a different combination, such as a master’s degree and 6years’ experience; a Ph.D. and 3 years’ experience in a related field; or 20 years’ experience in a related field
• 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

Preferred: 

• 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 
• Stro