Job Description
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.
Required Qualifications:
- 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.