Senior Data Engineer - Cloud & Real-Time Data Pipelines

Jobtailor; Colorado; On-site; USD 120,000 - 160,000; Full time

Job summary

Jobtailor in Colorado seeks a Senior Data Engineer to design and operate scalable data infrastructure across cloud and on-premises environments. You will collaborate with engineers, data scientists, and analytics teams in an agile setting to build data pipelines, APIs, and delivery services supporting analytics and ML applications.

The role emphasizes data quality, lineage, metadata management, and integration of data tools, with opportunities to lead architecture and modern DevOps practices

Qualifications

• Bachelor’s degree in computer science, math, engineering, or relevant technical field.
• 4+ years of collective experience in data engineering, data analytics, data warehousing, BI, database administration, and data integration concepts and methodologies.
• 3 years of experience architecting, building, and administering big data and real-time streaming analytics architectures in on-premises and cloud environments.
• 2 years of experience architecting, building, and administering large-scale distributed applications.
• 2 years of experience with Linux operations and development, including basic commands and shell scripting.
• 2 years of experience with DevOps methodologies and CI/CD.
• Expertise in SQL for data profiling, analysis, and extraction.
• Familiarity with data science techniques and frameworks.
• Strong analytical skills.
• Ability to work in a team environment.
• Strong technical communication skills.
• Ability to prioritize work to meet tight deadlines.
• Ability to learn and keep pace with the latest technology advances.
• Preferred: Master’s degree in a technical field.
• Preferred: Solid understanding of big data and real-time streaming analytics processing architecture and ecosystems.
• Preferred: Data warehousing architecture, source-to-target mappings, and ETL code.
• Preferred: Advanced analytics and ML concepts and implementations.
• Preferred: Data analysis and data visualization tools.
• Preferred: Certifications (AWS, Microsoft, etc.)
• Preferred: Software development experience in Java, Python, Scala, or Node.js
• Occasional travel under 10%

Responsibilities

• Work collaboratively with engineers, data scientists, analytics teams, and business product owners in an agile environment.
• Architect, build, and support Cloud and On-Premises enterprise data infrastructure and tools.
• Design robust, reusable, and scalable data-driven solutions and pipeline frameworks.
• Automate ingestion, processing, and delivery of structured and unstructured batch and real-time streaming data.
• Build data APIs and data delivery services for operational processes, analytical models, and ML applications.
• Assist in selecting and integrating data-related tools, frameworks, and applications.
• Implement best practices for master data, reference data, metadata, data quality, and data lineage.
• Support systems, services, and applications for enterprise data collection, storage, processing, and analysis.

Skills

Data Engineering

Big Data Architecture

SQL Proficiency

DevOps Methodologies

Data Warehousing

Data Integration

Data Pipeline Frameworks

Batch Processing

Real-Time Streaming Data

Linux Operations

Shell Scripting

Data Profiling

Data Analysis

Data Visualization Tools

Machine Learning Concepts

Cloud Infrastructure

CI/CD

Education

Bachelor’s degree in computer science, math, engineering, or relevant technical field

Master’s degree in a technical field (preferred)

Tools

AWS Certification

Microsoft Certification

CI/CD Tools

Cloud Infrastructure

Job description

Jobtailor in Colorado seeks a Senior Data Engineer to design and operate scalable data infrastructure across cloud and on-premises environments. You will collaborate with engineers, data scientists, and analytics teams in an agile setting to build data pipelines, APIs, and delivery services supporting analytics and ML applications.

The role emphasizes data quality, lineage, metadata management, and integration of data tools, with opportunities to lead architecture and modern DevOps practices