Data Systems & Integration Engineer

Vladimir Jones

Data Systems & Integration Engineer at Vladimir Jones designing and optimizing data pipelines. Responsible for data models and integrations to support client needs within a hybrid setup.

Posted 5/29/2026full-timeColorado Springs • Colorado • 🇺🇸 United StatesMid-LevelSenior💰 $75,000 - $90,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformHadoopJavaKafkaNoSQLPythonScalaSparkSQLSSIS

About the role

Key responsibilities & impact

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.
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.
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.
Document technical designs, workflows, and best practices to facilitate knowledge sharing and maintain system documentation.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field
Master's degree preferred
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
Proficiency in BI Tools such as NinjaCat, Data Studio, etc. preferred
Agency experience preferred.

Benefits

Comp & perks

401k + employer match
Medical, Dental, Vision
Life and short-term disability (100% employer paid)
Voluntary long-term disability
EAP
9 paid holidays
PTO, Floating Holiday, Volunteering Day
Education reimbursement
Employee referral program
Employee recognition program where points turn into money!

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringETLdata modelingSQLPythonJavaScalaHadoopSparkKafka

Soft Skills

problem-solvingattention to detailcommunicationcollaborationadaptability