Data Engineer & Insights Analyst

Location
Remote.

Experience Level
Mid–Senior Level (5+ years of relevant experience).

Role Overview
We are seeking a Data Engineer & Insights Analyst to transform complex data into trusted, usable information that supports program delivery, operational improvements, and executive decision-making. The role focuses on designing and building cloud-based data pipelines, integrating data from multiple sources, and addressing data quality issues. The analyst will also develop dashboards, reports, and analytical products that deliver actionable insights from large, confidential datasets. This position partners with data scientists, research and policy analysts, and cross-functional stakeholders, and supports data conversions tied to system modernization efforts.

Key Responsibilities

Data Pipeline Engineering & Cloud Solutions
• 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.
• Build the infrastructure required to extract, transform, and load data from a wide variety of sources using SQL and big data technologies.
• Assemble large, complex data sets that meet functional and non-functional business requirements.

Data Quality, Monitoring & Governance
• Develop and maintain pipeline monitoring, alerting, and logging frameworks.
• Implement data quality checks and validation frameworks across pipelines.
• Ensure compliance with applicable policies, data governance standards, privacy requirements, security controls, and data-sharing agreements.
• Automate manual processes, optimize data delivery, and redesign infrastructure for greater scalability.

Analytics & Insights Delivery
• Develop dashboards, reports, analytical models, and other decision-support products.
• Build analytics tools on top of the data pipeline to provide insights into education and workforce outcomes, operational efficiency, and key performance metrics.
• Engineer analytical data environments that support statistical analysis, predictive modeling, machine learning, and evidence-building activities.
• Create data tools that help analysts and data scientists build and optimize data products.

Collaboration & Delivery
• Partner with data scientists, research analysts, and policy analysts to support reproducible research and statistical modeling.
• Work with executive, data, design, and support teams to resolve data-related technical issues and meet data infrastructure needs.
• Support data conversions associated with system modernization or replacement efforts.

Required Qualifications
• 5+ years of hands-on experience with cloud-based data services such as AWS (S3, EC2, Glue, EMR, RDS, Redshift, Athena, Lambda, DynamoDB).
• 5+ years of proficiency in object-oriented or functional scripting languages such as Python, R, Java, C++, or Scala.
• 5+ years of proficiency in relational SQL and NoSQL databases, including Oracle, MS SQL Server, Postgres, and Cassandra, with advanced SQL and query authoring skills.
• 5+ years of experience with version control systems such as Git and CI/CD pipelines.
• 5+ years of knowledge of data modeling techniques, including dimensional modeling, data vault, and star/snowflake schemas.
• 5+ years of familiarity with data cataloging and metadata management tools such as AWS Glue Data Catalog.
• 5+ years of understanding of data governance, data lineage, and data quality frameworks.
• 5+ years of knowledge of REST API design and integration patterns.
• 5+ years of experience with big data tools such as Hadoop, Spark, and Kafka.
• 5+ years of experience with data pipeline and workflow management tools such as Azkaban, Luigi, and Airflow.
• 5+ years of experience with data integration solutions from vendors such as Informatica, MuleSoft, Talend, and TIBCO.
• 5+ years of experience with stream-processing systems such as Storm and Spark-Streaming.
• Experience building and optimizing big data pipelines, architectures, and data sets, including processes for data transformation, data structures, metadata, dependency, and workload management.
• Advanced 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 linking it to other sources such as employment and wage data to measure outcomes.
• Experience performing root-cause analysis on internal and external data and processes to answer business questions and identify improvement opportunities.
• Strong analytic skills with unstructured datasets and a history of extracting value from large, disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable big data stores.

Preferred Qualifications
• Experience with student-level higher education data and linkages to employment and wage data.
• Experience supporting data conversions associated with system modernization or replacement efforts.

Core Skills & Attributes
• Work in a self-directed manner while supporting the data needs of multiple teams, systems, and products.
• Apply strong analytical judgment when working with large, complex, and confidential datasets.
• Demonstrate strong project management and organizational skills.
• Collaborate effectively with cross-functional teams in a dynamic environment.
• Communicate insights clearly to executive and non-technical audiences.
• Pursue continuous improvement of data systems and functionality.