Data Engineer

A client of Robert Half is looking for a highly skilled Data Engineer to design, build, and optimize data pipelines and infrastructure that enable advanced analytics and business intelligence. The ideal candidate will have strong experience in big data technologies, cloud platforms, and hands-on expertise with Databricks. Key Responsibilities Data Pipeline Development: Design, develop, and maintain scalable ETL/ELT pipelines using Databricks and other tools. Integrate data from multiple sources into data lakes and warehouses. Data Architecture & Modeling: Implement robust data models for analytics and reporting. Ensure data quality, consistency, and governance across systems. Performance Optimization: Optimize Spark jobs and Databricks workflows for efficiency and cost-effectiveness. Monitor and troubleshoot data pipeline performance issues. Collaboration & Support: Work closely with data scientists, BI engineers, and business stakeholders to deliver data solutions. Provide technical guidance on best practices for data engineering and cloud architecture. Required Qualifications Bachelor’s degree in Computer Science, Information Systems, or related field. 7+ years of experience in data engineering and big data technologies. Strong proficiency in Databricks and Apache Spark. Expertise in SQL and relational databases (e.g., SQL Server, PostgreSQL). Experience with cloud platforms (AWS, Azure, or GCP) and their data services. Hands-on experience with data lake and data warehouse architectures. Proficiency in Python or Scala for data processing. Solid understanding of ETL/ELT processes and data governance principles. Preferred Skills Experience with Delta Lake and Lakehouse architecture. Familiarity with CI/CD pipelines for data workflows. Knowledge of big data tools (Kafka, Hadoop). Exposure to machine learning or advanced analytics.

The Data Engineer will design, develop, and maintain scalable ETL/ELT pipelines and ensure data quality and governance. They will collaborate with data scientists and business stakeholders to deliver effective data solutions.

Candidates must have a bachelor's degree and over 7 years of experience in data engineering, with strong proficiency in Databricks and big data technologies. Expertise in SQL, cloud platforms, and data processing languages like Python or Scala is also required.

Identified from the job description. Confirm important requirements above.

• Data Engineering
• Big Data Technologies
• Databricks
• Apache Spark
• SQL
• Relational Databases
• Cloud Platforms
• AWS
• Azure
• GCP
• Data Lake
• Data Warehouse
• Python
• Scala
• ETL
• Data Governance

• Technology
• Data & Analytics
• Retail
• Software

Minimum education

Bachelor’s degree

Minimum experience

10+ years

Apply by

Aug 14, 2026

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available