Data Engineer & Insights Analyst

LingaTech; Harrisburg (Dauphin County); Remote; USD 120,000 - 180,000; Full time

Job summary

LingaTech is seeking a Data Engineer & Insights Analyst to design, develop, and maintain scalable data infrastructure and analytical solutions. The role supports program delivery, research initiatives, and executive decision-making through cloud-based data pipelines and analytics products.

Ideal candidates will combine strong data engineering skills with analytical judgment, supporting data modernization, system integration, and data-driven initiatives across teams.

Qualifications

• Extensive experience designing data pipelines and ETL architectures.
• Proficiency with AWS data services and cloud-based solutions.
• Strong SQL, NoSQL, and data modeling knowledge.
• Experience with data governance, lineage, and quality frameworks.
• Familiarity with data orchestration tools like Airflow.

Responsibilities

• Design and maintain scalable data pipelines for analytics.
• Implement cloud-based data solutions using AWS services.
• Develop orchestration workflows with Airflow and similar tools.
• Integrate and load data from multiple sources via SQL and big data tech.
• Create dashboards and analytics products for stakeholders.
• Ensure data governance, privacy, and security compliance.

Skills

Cloud AWS

Python

SQL

Data modeling

Airflow

CI/CD

Big data

REST APIs

Data governance

Data quality

Tools

Apache Airflow

Spark

Hadoop

Kafka

Talend

Informatica

AWS Glue Data Catalog

Job description

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.