Data Engineer & Insights Analyst

VIVA USA Inc; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

VIVA USA Inc is seeking a Data Engineer & Insights Analyst to transform complex data into trusted information for state government program delivery and executive decision-making. You will design and build data pipelines, integrate data from multiple sources, and establish quality controls to support data-driven decisions.

You will work with data scientists, policy and support teams to ensure reproducible research, scalable infrastructure, and data governance across platforms in a remote-friendly

Qualifications

• Hands-on with cloud-based data services including AWS (S3, EC2, Glue, EMR, Redshift, Athena, Lambda).
• Proficiency in Python, R, Java, or Scala for data engineering tasks.
• Strong SQL and NoSQL database skills across Oracle, MS SQL Server, PostgreSQL, Cassandra.
• Experience with Git and CI/CD pipelines for code management.
• Knowledge of dimensional, data vault, and star/snowflake modeling.
• Familiarity with AWS Glue Data Catalog for metadata management.
• Understanding of data governance, lineage, and quality frameworks.
• REST API design and integration patterns familiarity.
• Experience with Hadoop, Spark, Kafka for big data processing.
• Experience with Airflow, Azkaban, Luigi for workflows.
• Experience with ETL tools: Informatica, MuleSoft, Talend, TIBCO.
• Experience with stream-processing systems such as Storm, Spark-Streaming.

Responsibilities

• Create and maintain optimal data pipeline architecture.
• Design and implement cloud-based data solutions using AWS services.
• Build and maintain data orchestration workflows with Airflow or similar.
• Assemble large, complex data sets meeting business requirements.
• Engineer data environments to support advanced analytics and modeling.
• Collaborate with data scientists and policy analysts to ensure reproducible research.
• Identify internal process improvements and optimize data delivery.
• Build infrastructure for ETL from diverse data sources using SQL and big data tech.
• Develop dashboards, reports, and decision-support products.
• Ensure data governance, privacy, and security controls compliance.

Skills

AWS Data Services

Programming languages

SQL/NoSQL Databases

Git & CI/CD

Data Modeling

AWS Glue Data Catalog

Data Governance & Quality

REST API Design

Big Data: Hadoop/Spark/Kafka

Airflow/Luigi/Azkaban

Data Integration: Informatica/MuleSoft

Stream Processing: Storm/Spark-Stream

Job description

Remote

The client is looking for a Data Engineer & Insights Analyst to join its team of analytics professionals to support the client Longitudinal Data System (LDS). This position will be responsible for transforming complex data into trusted, usable information to support program delivery, operational improvements, and executive decision‑making in state government agencies. The Data Engineer & Insights Analyst will understand policy‑relevant research questions, evaluate available data sources, and develop analytics products to deliver actionable insights. Additionally, the Data Engineer & Insights Analyst will design and build data pipelines, integrate and transform data from multiple sources, identify and address data quality issues, and establish controls to support responsible use of data. This role requires both technical depth and strong analytical judgment, including the ability to work with large, complex, and confidential datasets. The successful candidate must be self‑directed and comfortable supporting the data needs of multiple teams, systems, and products. They must also be comfortable with supporting data conversions associated with system modernization and/or replacement efforts. The right candidate will be excited by the prospect of optimizing the Commonwealth's longitudinal data architecture to support our next generation of data initiatives.

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.

Skill - Required / Desired - Amount of Experience

• Hands‑on experience with cloud‑based data services such as AWS (e.g. S3, EC2, Glue, EMR, RDS, Redshift, Athena, Lambda, DynamoDB) - Required - 5 Years
• Proficiency in object‑oriented/object function scripting languages: e.g. Python, R, Java, C++, Scala - Required - 5 Years
• Proficiency in relational SQL and NoSQL databases, including Oracle, MS SQL Server, Postgres, Cassandra. - Required - 5 Years
• Experience with version control systems such as Git and CI/CD pipelines - Required - 5 Years
• Knowledge of data modeling techniques including dimensional modeling, data vault, and star/snowflake schemas. - Required - 5 Years
• Familiarity with data cataloging and metadata management tools such as AWS Glue Data Catalog. - Required - 5 Years
• Understanding of data governance, data lineage, and data quality frameworks. - Required - 5 Years
• Knowledge of REST API design and integration patterns. - Required - 5 Years
• Experience with big data tools: e.g. Hadoop, Spark, Kafka. - Required - 5 Years
• Experience with data pipeline and workflow management tools: e.g. Azkaban, Luigi, Airflow. - Required - 5 Years
• Experience with data integration services solutions from vendors such as Informatica, MuleSoft, Talend, and TIBCO. - Required - 5 Years
• Experience with stream-processing systems: e.g. Storm, Spark-Streaming. - Required - 5 Years

Notes

Work will be remote.

VIVA is an equal opportunity employer. All qualified applicants have an equal opportunity for placement, and all employees have an equal opportunity to develop on the job. This means that VIVA will not discriminate against any employee or qualified applicant on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status