Data Systems & Integration Engineer

Vladimir Jones•Colorado Springs, CO

1d•$75,000 - $90,000•Hybrid

About The Position

Vladimir Jones is seeking a highly skilled and motivated Data Systems & Integration Engineer to join our innovative team. You will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support our data-driven initiatives to include traditional dataflows and AI integrations. You will collaborate closely with cross-functional teams to ensure the availability, reliability, and performance of our data systems and solutions in support of our clients.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
Proven experience in data engineering, software development, or related roles.
Proficiency in programming languages commonly used in data engineering (e.g., Python, Java, Scala, etc.).
Use data analytics software (SQL, SAS, R, etc.) to clean and organize large data sets to be used in analyses
Design, diagnose, and deploy statistical models to analyze and interpret data using a statistical software package such as R, SAS, or Stata
Strong knowledge of database systems, data modeling techniques, and SQL proficiency.
Proficiency with ETL tools commonly used in data engineering (e.g., SSIS, Databricks, etc.).
Experience with big data technologies and frameworks (e.g., Hadoop, Spark, Kafka, etc.).
Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud Platform, etc.).
Excellent problem-solving skills and attention to detail.
Effective communication and collaboration skills in a team-oriented environment.
Ability to adapt to evolving technologies and business requirements.

Nice To Haves

Master's degree preferred.
Familiarity with modeling techniques such as Bayesian Marketing Mix Modeling, Machine Learning-Based and Agentic Derived MMM, and Performance & Attribution Models.
Proficiency in BI Tools such as NinjaCat, Data Studio, etc. preferred.
Agency experience preferred.

Responsibilities

Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
Develop robust ETL (Extract, Transform, Load) processes to integrate data from diverse sources into our data ecosystem.
Implement data validation and quality checks to ensure accuracy and consistency.
Design and maintain data models, schemas, and database structures to support analytical and operational use cases.
Optimize data storage and retrieval mechanisms for performance and scalability.
Evaluate and implement data storage solutions, including relational databases, NoSQL databases, data lakes, and cloud storage services.
Maintain dataset integrity and optimize builds to work in AI Agent and BI Visualizations.
Build and maintain integrations with internal and external data sources and APIs.
Integrate agency AI initiatives into workflow processes and dataflows.
Implement RESTful APIs and web services for data access and consumption.
Ensure compatibility and interoperability between different systems and platforms.
Configure and manage data infrastructure components, including databases, data warehouses, data lakes, and distributed computing frameworks.
Monitor system performance, troubleshoot issues, and implement optimizations to enhance reliability and efficiency.
Implement data security controls and access management policies to protect sensitive information.
Collaborate with analysts and other stakeholders to understand data requirements and deliver tailored solutions.
Document technical designs, workflows, and best practices to facilitate knowledge sharing and maintain system documentation.
Provide technical guidance and support to team members and stakeholders as needed.
Maintain proper governance of Data and AI initiatives to properly protect client and company data privacy.
Stay aware of federal and state regulations in regards to data privacy and protection standards.