Senior Data Engineer

Location: Remote - US

Department: Data Labs

Location Type: REMOTE

Employment Type: FULL_TIME

• Design, build, and maintain scalable data pipelines that support reporting, analytics, and platform needs across Daxko's product lines
• Own data architecture decisions at the product level, including schema design, data modeling, and ETL/ELT strategy using Kimball dimensional modeling and star-schema patterns
• Identify pipeline bottlenecks and performance gaps, then implement durable fixes that improve data reliability and freshness
• Lead and contribute to code and design reviews, giving actionable feedback grounded in data engineering best practices
• Partner cross-functionally with Data Science, Product, and Engineering to expand how data is understood and used across the organization
• Mentor junior and mid-level engineers, shaping team standards and driving a culture of technical quality
• Evaluate and adopt emerging data tools and methodologies to improve team velocity and platform capability

• 4+ years of experience in data engineering or a closely related software engineering discipline
• Expert-level SQL/TSQL skills and deep experience with query optimization and data storage
• Proficiency in Python for pipeline and application development
• Hands-on experience with columnar databases and cloud-native platforms such as Snowflake, Amazon Redshift, or Databricks
• Experience designing ETL/ELT workflows and dimensional data models (Kimball methodology is a strong plus)
• A track record of writing well-tested, production-grade code and working within Agile delivery frameworks
• Clear communication skills, with the ability to explain complex data decisions to both technical and non-technical stakeholders

• 7+ years of experience in data engineering or software engineering with a data focus
• Experience with modern data platform tooling such as dbt, Airflow, or Spark
• Familiarity with real-time streaming platforms (Kafka, Kinesis) or serverless query solutions (Athena, Redshift Spectrum)
• Experience with containerization (Docker, Kubernetes), REST APIs, or AWS services such as Lambda, SNS, or SQS