Senior Data Engineer — AWS Cloud Pipelines & Analytics

Cloud Analytics Technologies, LLC; Raleigh (NC); On-site; USD 120,000 - 180,000; Full time

Job summary

Cloud Analytics Technologies, LLC, a Raleigh-based data engineering firm, seeks a senior data engineer to design scalable data pipelines and analytics platforms.

You will collaborate with data scientists and policy teams to deliver insights using AWS, Airflow, and large-scale datasets. The role emphasizes building robust data quality controls and governance to support reproducible research and decision-making.

Qualifications

• 12+ years of data engineering experience with advanced SQL and relational databases.
• Experience building and optimizing big data pipelines, architectures and datasets.
• Advanced knowledge in designing dashboards, reports, analytical models and decision-support tools for executives and non-technical users.
• Experience with student-level higher education data and linking sources to measure outcomes.
• Root-cause analysis on data and processes to identify improvements.
• Working knowledge of handling unstructured datasets and data quality checks.

Responsibilities

• Create and maintain optimal data pipeline architecture.
• Design and implement cloud-based data solutions using AWS services (S3, Glue, Redshift, EMR, Athena, Kinesis, Lambda).
• Build and maintain data orchestration workflows (Airflow, Step Functions).
• Assemble large, complex data sets meeting business requirements.
• Engineer environments supporting advanced statistical analysis, ML, and evidence-building."
• Partner with data scientists and policy analysts to ensure reproducible research and modeling.

Skills

Advanced SQL

Relational databases

Big data pipelines

Dashboard design

Unstructured data

Data transformation

Tools

Apache Airflow

AWS Glue

AWS Redshift

AWS EMR

Job description

Cloud Analytics Technologies, LLC, a Raleigh-based data engineering firm, seeks a senior data engineer to design scalable data pipelines and analytics platforms.

You will collaborate with data scientists and policy teams to deliver insights using AWS, Airflow, and large-scale datasets. The role emphasizes building robust data quality controls and governance to support reproducible research and decision-making.