Data Engineer Technology

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, o...