Data Engineer – Customer Data
Job Type: Full Time / Permanent
What you will bring: Experience and love for Python, Spark, SQL, or other standard data scripting languages. Hands-on experience building, managing, and automating data pipelines. Familiarity and appreciation for modern public cloud data services from AWS, GCP, or Azure. 3+ years of experience being close to the business and delivering value through it as part of a team. Some knowledge or exposure to supporting AI/ML engineering and integrating data to model development, management and serving. A good grip of data structures, relationships, integration patterns, and algorithms. General understanding of data warehousing principles, documentation practices, refactoring, scalability, and testing techniques. Experience working in an agile environment utilizing tools such as Jira, Confluance, and GitHub. You understand the importance of Kafka, Snowpipe, or Kinesis for real-time needs. Some experience applying security and privacy to how you manage data. A grasp of the importance of common data platform patterns and how they relate like Data Lake, Data Mesh, Data Catalog, Tagging, Stream Processing, etc.
Job Duties & Responsibilities: Work as part of a team building the data ingestion, products, pipelines, and tooling supporting our Customer Hub data product driving Marketing, Retail, E-commerce, and Enterprise initiatives. Work with stakeholders including the product, data and architecture teams to assist with data-related technical issues and support their data infrastructure needs. Provide proactive design, operational support, and governance for privacy and security policy for data.
Education & Experience: Bachelor’s Degree in Computer Science, Software Engineering, Information Systems or Information Technology or related field required, or equivalent experience 3-5 years of experience in Data Engineering, AI/ML Engineer Integration, Data Modeling. Any Public Cloud certification focused on Data Engineering or Data Science. Any Public Cloud certification focused on Cloud Engineering. Experience building data pipelines on modern public cloud services like Snowflake, AWS, GCP, or Azure. Experience with message queuing, stream processing, and highly scalable ‘big data’ data stores (Kafka, Pub/Sub). Proficient with SQL Experience with Cloud Identity and Access Management for data on public cloud. Proficient with object-oriented programming and scripting languages (Python, Java, etc.). Experience with continuous integration/continuous delivery (CI/CD) pipelines (Jenkins, Concourse, Azure DevOps). Experience with relational databases (Oracle, SQL Server, etc.) as well as NoSQL database technologies (MongoDB, BigTable, Cassandra, etc.). Experience with Agile Development and Agile Deployment tools and versioning using Git or similar tools Proficient in developing, maintaining and interacting with APIs Proficient in Linux/Unix environments.