Data Engineer

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

Job summary

Artifintech in Raleigh seeks a Data Engineer with 12+ years to own and optimize complex data pipelines, build cloud data solutions on AWS, and deliver scalable analytics for executive decision-making.

You will collaborate with data scientists, policy analysts, and cross-functional teams to ensure data governance, quality, and reproducible research, leveraging tools like Airflow and Redshift.

Qualifications

• Data engineer with 12+ years of experience and deep SQL knowledge.
• Extensive experience building and optimizing big data pipelines and datasets.
• Proficient in designing dashboards and analytical models for executives.
• Experience handling student-level higher education data and linking sources to measure outcomes.
• Strong root-cause analysis and insight generation from complex data.
• Experience with unstructured data and data transformation processes.
• Experience building scalable data architectures and data workflows.
• Familiarity with message queues and streaming data.
• Excellent project management and cross-functional collaboration.
• Ability to ensure governance, privacy, and security controls.

Responsibilities

• Create and maintain optimal data pipeline architecture.
• Design and implement cloud-based data solutions using AWS services (S3, Glue, Redshift, EMR).
• Build and maintain data orchestration workflows with Airflow or similar.
• Assemble large, complex data sets meeting business requirements.
• Engineer analytical data environments that support advanced statistical analysis and machine learning.
• Partner with data scientists and policy analysts to ensure reproducible research and data assets.
• Identify and implement internal process improvements for scalability.
• Build ETL processes for diverse data sources using SQL and big data tech.
• Build analytics tools to derive actionable insights on education and workforce outcomes.
• Develop data quality checks and monitoring frameworks.
• Develop dashboards, reports, and decision-support products.
• Work with stakeholders to address data infrastructure needs and governance.

Skills

Advanced SQL

Relational databases

Big data pipelines

Dashboard design

Data transformation

Data quality

Workflow orchestration

AWS

Airflow

Data governance

Tools

Apache Airflow

AWS

AWS Glue

Redshift

S3

EMR

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Work Authorization:US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:

Required Qualifications:

• Data engineer with12+ years’ experience in Advanced SQL knowledge and proficiency working with relational databases, query authoring (SQL), as well as working familiarity with a variety of databases.


• Experience building and optimizing 'big data' data pipelines, architectures, and data sets.


• Advanced knowledge and proficiency designing, building, and refining dashboards, reports, analytical models, and decision-support products for executive and non-technical users.


• Experience working with student-level higher education data, including establishing linkages to other sources (e.g. employment and wage data) to measure outcomes and/or generate insights for decision-making).


• Experience performing root-cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.


• Strong analytic skills related to working with unstructured datasets.


• Experience building processes supporting data transformation, data structures, metadata, dependency, and workload management.


• A successful history of manipulating, processing, and extracting value from large, disconnected datasets.


• Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.


• Strong project management and organizational skills.


• Experience supporting and working with cross-functional teams in a dynamic environment.

Responsibilities:

• Create and maintain optimal data pipeline architecture.


• Design and implement cloud-based data solutions using AWS services such as S3, Glue, Redshift, EMR, Athena, Kinesis, and Lambda.


• Build and maintain data orchestration workflows using tools such as Apache Airflow, AWS Step Functions, or similar services.


• Assemble large, complex data sets that meet functional / non-functional business area requirements.


• Engineer analytical data environments that support advanced statistical analysis, predictive modeling, machine learning, and evidence-building activities.


• Partner with data scientists, research analysts, and policy analysts to ensure enterprise data assets support reproducible research and statistical modeling.


• Identify, design, and implement internal process improvements: e.g. automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.


• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and 'big data' technologies.


• Build analytics tools that utilize the data pipeline to provide actionable insights into education and workforce outcomes, operational efficiency, and other key business performance metrics.


• Develop and maintain data pipeline monitoring, alerting, and logging frameworks.


• Implement data quality checks and validation frameworks across pipelines.


• Develop dashboards, reports, analytical models, and/or other decision-support products.


• Work with stakeholders including the Executive, Data, Design, and Support teams to assist with data-related technical issues and support their data infrastructure needs.


• Ensure compliance with applicable Commonwealth policies, data governance standards, privacy requirements, security controls, and interagency data-sharing agreements.


• Create data tools for analytics and data scientist team members that assist them in building and optimizing data products needed to support ongoing operations and data-informed decision-making.


• Work with data and analytics professionals to strive for greater functionality in our data systems.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.