About this role
Position Summary:
Data Engineer - Technology
We are seeking a Data Engineer to help build and modernize our data pipeline architecture. The immediate mission: support the migration of ETL workloads out of Redshift stored procedures and legacy SSIS packages into scalable, maintainable pipelines using AWS Glue and S3. The longer-term vision: help us evolve from batch-oriented processing toward near real-time analytics using stream processing technologies like Apache Flink and ClickHouse, among others. You will be embedded in a cross-functional engineering team, working alongside senior engineers to build pipelines and grow your expertise in modern cloud-native data architecture.
Objectives:
• Build and maintain modern ETL/ELT pipelines using AWS Glue, S3, and related services to help replace legacy stored procedures and SSIS jobs. • Develop data transformation workflows that are testable, version-controlled, and observable. • Help maintain our Redshift data warehouse, including materialized views, query performance, and cost efficiency. • Support the evolution from batch ETL to near real-time stream processing, assisting with the evaluation and implementation of technologies such as Apache Flink, ClickHouse, Kafka, Kinesis, or equivalent platforms. • Design pipelines that support both near real-time and batch workloads as the platform transitions. • Collaborate with product and analytics teams to help ensure data models support reporting, AI/ML, and customer-facing features. • Follow and help refine established patterns and best practices for pipeline development. • Participate in production support and incident response for data infrastructure.
Requirements:
Education/Experience:
• Bachelor's degree in Computer Science, Engineering, or related field. 2-4 years of experience in data engineering roles.
Skills:
• Working experience with AWS Glue (PySpark/Python), S3, and Redshift. Docusign Envelope ID: 3DB5DE32-5404-82BD-80A4-A92CE5E89F74 • Hands-on experience migrating or supporting the migration of ETL workloads from legacy tools (SSIS, stored procedures, or similar) to modern cloud-native pipelines. • Strong SQL skills with best practices and SQL linting, particularly in Redshift or other columnar/MPP databases. • Experience with or strong interest in stream processing frameworks (Flink, Spark Streaming, Kafka Streams, or similar). • Familiarity with data pipeline orchestration, monitoring, and error handling patterns. • Familiarity with infrastructure-as-code and CI/CD concepts as applied to data pipelines.
Desired Skills:
• Experience with Aurora MySQL or other relational databases, and NoSQL such as DynamoDB. • Hands-on experience with near real-time OLAP engines (ClickHouse, Apache Druid, or similar). • Exposure to streaming data infrastructure (Kinesis, Kafka, MQTT). • Familiarity with IoT or utility/metering data. • Experience with dbt, Airflow, or Step Functions. • Strong communication skills, with the ability to explain complex data architecture concepts to technical and non-technical stakeholders. • A working understanding of software development methodologies (Agile, Scrum, etc.). • Strong problem-solving abilities and a drive for results.
Location: • Tallassee, Alabama or Duluth, Georgia; May be required to travel to one of our manufacturing/customer locations up to 20% of the time when necessary.
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