Data Engineer

Jobtailor; Denver (CO); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor seeks a senior data engineer to design and implement Databricks Lakehouse solutions for diverse clients. You will collaborate with stakeholders, gather requirements, and deliver scalable data pipelines.

You will apply data modeling, governance, and cloud architecture principles, with hands-on expertise in PySpark, SQL, Delta Lake, and Unity Catalog, in a client-facing consulting context.

Qualifications

• 7+ years of IT experience.
• Databricks (data engineering, SQL, notebooks, app/backend integration patterns).
• Enterprise data warehouses and lakehouse platforms (Nice to have Fabric, Snowflake, Synapse, BigQuery – experience).
• Deep knowledge of data modeling, data warehousing, and lakehouse patterns.
• Hands-on experience with at least one modern data platform.
• Experience integrating data platforms with applications using APIs, services, or event-driven patterns.
• Cloud architecture concepts (security, networking, scalability, cost management).
• Strong communication skills with the ability to engage both technical and business stakeholders.
• Experience in client-facing or consulting environments.
• 4+ years of experience in cloud/infrastructure technologies and/or related fields.
• Deep hands on experience with Databricks Lakehouse Platform and Apache Spark.
• Strong proficiency in PySpark, SQL, Delta Lake, Databricks SQL.
• Experience implementing Unity Catalog, data governance, and enterprise security controls.
• Cloud experience with Azure Databricks, AWS Databricks, or GCP Databricks.
• Familiarity with CI/CD, DevOps, and automation for Databricks workloads.
• 8–12+ years in data engineering or architecture, with 4–5+ years delivering Databricks solutions.
• Proven experience in client facing consulting roles, including requirements discovery, solution design, and executive communication.

Responsibilities

• Develop and manage data engineering solutions involving Databricks Lakehouse Platform
• Collaborate with clients and stakeholders to gather requirements and feedback
• Ensure data integrity and implement data governance practices
• Design architecture for data processing and storage solutions
• Work in consulting environments to deliver services and solutions to clients

Skills

Databricks Lakehouse Platform

Data Engineering

SQL

Data Governance

Cloud Architecture

PySpark

Delta Lake

Databricks SQL

APIs

Event-Driven Patterns

CI/CD

DevOps

Cloud Technologies

Education

Bachelor's Degree in Computer Science, Information Technology, Engineering, Business

Tools

Azure Databricks

AWS Databricks

GCP Databricks

Apache Spark

Unity Catalog

Job description

• Develop and manage data engineering solutions involving Databricks Lakehouse Platform
• Collaborate with clients and stakeholders to gather requirements and feedback
• Ensure data integrity and implement data governance practices
• Design architecture for data processing and storage solutions
• Work in consulting environments to deliver services and solutions to clients

Requirements

• 7 + years of IT experience
• Databricks (data engineering, SQL, notebooks, app/backend integration patterns)
• Enterprise data warehouses and lakehouse platforms (Nice to have Fabric, Snowflake, Synapse, BigQuery – experience)
• Deep knowledge of data modeling, data warehousing, and lakehouse patterns
• Hands‑on experience with at least one modern data platform
• Experience integrating data platforms with applications using APIs, services, or event‑driven patterns
• Solid understanding of cloud architecture concepts (security, networking, scalability, cost management)
• Strong communication skills with the ability to engage both technical and business stakeholders
• Experience working in client‑facing or consulting environments
• Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, or related field
• 4+ years of experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting
• Deep hands on experience with Databricks Lakehouse Platform and Apache Spark
• Strong proficiency in PySpark, SQL, Delta Lake, Databricks SQL
• Experience implementing Unity Catalog, data governance, and enterprise security controls
• Cloud experience with Azure Databricks, AWS Databricks, or GCP Databricks
• Familiarity with CI/CD, DevOps, and automation for Databricks workloads
• 8–12+ years in data engineering or architecture, with 4–5+ years delivering Databricks solutions
• Proven experience in client facing consulting roles, including requirements discovery, solution design, and executive communication.

Core Competencies

Demonstrates extensive expertise in data engineering solutions, particularly with the Databricks Lakehouse Platform, and possesses strong skills in data governance, architecture design, and client engagement in consulting environments.

Highest-signal resume keywords

• Databricks Lakehouse Platform
• Data Engineering
• SQL
• Data Governance
• Cloud Architecture

ATS Optimization Keywords

Hard Skills

• Data Modeling
• Data Warehousing
• PySpark
• Delta Lake
• Databricks SQL
• API Integration
• Event-Driven Patterns
• CI/CD
• DevOps
• Cloud Technologies

Soft Skills

• Strong Communication Skills
• Client Engagement

Certifications & Qualifications

• Bachelor's Degree in Computer Science
• Information Technology
• Engineering
• Business

Industry Keywords

• Data Engineering
• Consulting
• Enterprise Data Warehouses
• Lakehouse Patterns
• Data Governance Practices

Tools & Technologies

• Azure Databricks
• AWS Databricks
• GCP Databricks
• Apache Spark
• Unity Catalog