Data Engineer & Insights Analyst

Job Type: Remote

Job Overview

The Data Engineer & Insights Analyst will design, develop, and maintain data infrastructure and analytical solutions that transform complex, multi-source datasets into reliable, actionable information. This role supports program delivery, operational improvements, research initiatives, and executive decision-making through the development of scalable data pipelines, cloud-based data solutions, and analytical products. The ideal candidate combines strong technical expertise in data engineering with analytical judgment and the ability to support data modernization, system integration, and data-driven initiatives across multiple teams.

Job Duties & Responsibilities

• Design, develop, and maintain scalable data pipeline architectures to support enterprise data and analytics initiatives.

• Implement cloud-based data solutions using AWS services, including S3, Glue, Redshift, EMR, Athena, Kinesis, and Lambda.

• Develop and maintain data orchestration workflows using Apache Airflow, AWS Step Functions, or comparable technologies.

• Integrate, extract, transform, and load large, complex datasets from multiple sources using SQL and big data technologies.

• Build and optimize analytical data environments that support statistical analysis, predictive modeling, machine learning, and research initiatives.

• Collaborate with data scientists, research analysts, and policy analysts to develop reliable data assets that support reproducible research and statistical modeling.

• Identify and implement process improvements through automation, infrastructure optimization, and more efficient data delivery methods.

• Develop analytics tools and data products that provide actionable insights into education and workforce outcomes, operational efficiency, and key performance metrics.

• Establish and maintain data pipeline monitoring, alerting, logging, data quality checks, and validation frameworks.

• Develop dashboards, reports, analytical models, and other decision-support products for technical and non-technical stakeholders.

• Perform data analysis and troubleshooting to identify data quality issues, investigate root causes, and improve the reliability of data processes.

• Support data conversions and integrations associated with system modernization and replacement initiatives.

• Partner with executive, data, design, and support teams to address technical issues and support enterprise data infrastructure needs.

• Develop tools and resources that help analytics and data science teams build, maintain, and optimize data products.

• Ensure data solutions comply with applicable data governance standards, privacy requirements, security controls, organizational policies, and interagency data-sharing agreements.

• Continuously evaluate and improve data systems, architecture, and processes to support evolving business and analytical needs.

Job Requirements

Required Skills & Experience

• 5 years of hands-on experience with cloud-based data services such as AWS (e.g., S3, EC2, Glue, EMR, RDS, Redshift, Athena, Lambda, DynamoDB).

• 5 years of proficiency in object-oriented/object-function 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, PostgreSQL, and Cassandra.

• 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.