Job description
Chick-fil-A has successfully implemented a modern cloud-native, self-service data ecosystem comprised of AWS S3, Glue, Redshift and Databricks. In this role you will drive the design and implementation of the software components and features required to evolve it into the next-generation architecture meeting the needs of data engineers throughout Chick-fil-A.
You will be responsible for architecting, designing, and leading the implementation of features for metadata management as well as advanced data management components related to our enterprise data lake, data warehouses, Spark platform, and other relational and non-relational data stores. Integration between components to deliver the best possible developer experience is key.
Your daily work will require partnering with fellow engineers, the product owner, data and enterprise architects, stakeholders, vendor teams, and other parties following an agile methodology, while being part of a diverse team that values high performance and excellence as much as work-life balance.
This role is based in the Atlanta, GA area. Relocation available for the selected candidate.
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.
- Lead, mentor and assess multiple partner engineering teams with minimal supervision
- Identify opportunities to improve the developer experience then design and architect revisions to reduce friction in the user experience.
- Partner with data scientists and data engineers to fully understand emerging needs and unmet needs. Collaborate and promote value-based adoption.
- Review the work of multiple partner led pods – ensuring conformance to standards, adoption of patterns, sound designs and good development practices.
- Exercise skills in cloud infrastructure and deployment as well as areas like application security, data analytics, machine learning, and site reliability engineering (SRE)
- Define patterns and processes for data transformation, movement, and manipulation using (among others) Hadoop/Spark, SQL, Airflow, Databricks, Amazon Aurora, DynamoDB, Athena, Redshift, ML libraries/tools
- Identify & propose emerging technologies, methodologies and/or approaches related to data and analytics
- Be a key participant of the team’s Agile process
- Address engineering assignments by autonomously deciding which ones to delegate and which ones to execute hands-on
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. The goal is to design for failure and, using cloud-native infrastructure patterns, automate responses to issues so they can be worked during normal hours.
Minimum Qualifications:- 5+ years or more related work experience
- Master’s degree in Computer Science, Analytics Engineering or related technical field or the equivalent combination of education, training and experience from which comparable skills have been acquired
- Broad and deep programming experience in Python, JavaScript, Java, Scala, or other comparable languages
- Experience with SQL, data modeling, and the Hadoop ecosystem
- Experience with source-control systems like Git or Subversion, and CI/CD tools like GitHub Actions or Jenkins
- Experience implementing application security, software design patterns, and the SDLC
- Good interpersonal and team collaboration skills
- Experience architecting software solutions on Amazon Web Services (AWS) or other major CSP
- Experience working with an Agile development methodology featuring sprints, point-estimation, and daily standups
- Proficiency in Spark programming or equivalent big data technology
- Experience with Unix/Linux and container technologies such as Docker
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