Sr. Lead Software Engineer, Analytics

Overview:

Working with confidential data, an understanding of designing secured systems and segmenting user access is required.

In the delivery of these solutions, you will be serving to both oversee your team and contribute as a member. You will not be responsible for HR management of your team, though –you’ll rather be able to focus on the technical aspects of your team’s growth and delivery.

Our Flexible Future model offers a healthy mix of working in person and virtually, strengthening key elements of the Chick-fil-A culture by fostering collaboration and community.

Responsibilities:

Software Engineering:

• Coordinate with the Technical Product Owner to understand what needs to be built and break requirements down into technical stories on which your team can execute.
• Lead delivery and operations of the team’s solutions, including both individual contribution and support as well as delegated tasks and support to your team’s engineers. We desire our lead engineers to be both leads and engineers, spending about half of their time on leading others and half contributing engineering work themselves.
• Lead, mentor, and assess other staff engineers, exemplifying and teaching best practices, helping to solve knotty problems, and reviewing code.
• Interview, select, onboard, and oversee other engineers.
• Guide engineering team in adoption of Chick-fil-A software engineering standards.
• Identify & propose emerging software engineering technologies, methodologies and/or approaches.

Data Architecture:

• Design and implement scalable, robust, and secured data architectures, including data lakes, data warehouses, and real-time data pipelines.
• Operate and manage modern data and analytics platforms.
• Design a system for and support user segmented security to control access to data sets.

ETL Development:

• Build and maintain efficient and reliable ETL pipelines to ingest, transform, and load data from various sources. Ingestion will include working with REST APIs. Transformation and storage will include encrypting for confidential data.
• Continuously improve the performance, scalability, and reliability of data pipelines.

Database Management:

• Work with a variety of database technologies, both SQL and NoSQL, ensuring optimal performance, data integrity, and user segmented security of datasets.

Note - Working in a DevOps model, this opportunity includes both building and running solutions that could require off-hours support. This support is shared amongst the team members to cover weekends and weeknights.

Minimum Qualifications:

• Broad and deep programming experience in Python programming.
• Experience working with analytics platforms (e.g., Databricks)
• Experience with data technologies in AWS or other cloud-based data platforms.
• Expertise in designing, building, and maintaining ETL pipelines.
• Experience working with both SQL and NoSQL databases.
• Demonstrated leadership skills and experience.
• Demonstrated ability to communicate complex technical information in a condensed manner to various stakeholders verbally and in writing.
• Strong organizational skills, including an ability to perform under pressure and manage multiple priorities with competing demands for resources.
• Experience designing complex software solutions.
• Experience mentoring and leading a team, including good interpersonal and team collaboration skills.
• Experience with source control systems like Git.
• Experience implementing application security, software design patterns, and the SDLC.
• Proven ability to positively influence the engineering culture and practices in a professional environment.
• Experience with TDD, CI/CD, agile, Kanban, or similar software development practices.
• Experience working in an Agile/Scrum development environment.

Preferred Qualifications:

• 7+ years of experience in software engineering.
• 5+ years of experience in the technical oversight of software engineering teams.
• 3+ years of hands-on experience with Databricks.
• Broad and deep programming experience in Python programming, including experience with data engineering libraries like Pandas and PySpark.
• Experience working with data integration technologies such as Spark.
• Deep understanding of database concepts, data structures, and data modeling principles.
• Experience managing infrastructure automation using Terraform.
• Knowledge of data visualization tools (e.g., Tableau).

Minimum Years of Experience: 5

Required Level of Education: Bachelor's degree or equivalent experience

Preferred Level of Education: Bachelor's Degree

Major/Concentration: Computer Science/Computer Engineering