Explore Data Warehouse and ETL Developer Jobs

Data Warehouse and ETL Developers design and maintain the systems that move, organize, and prepare data for analytics and business operations. Browse vetted opportunities on Ladders, including roles paying $100,000 or more, and find positions that match your technical expertise and career goals.

What Data Warehouse and ETL Developers Do

These professionals build data warehouses and pipelines that bring information together from databases, applications, and other sources. Typical responsibilities include developing extract, transform, and load (ETL) or extract, load, and transform (ELT) workflows; modeling and validating data; improving performance and reliability; and supporting reporting and analytics teams.

Skills and Technologies Employers Seek

Job requirements vary, but employers commonly seek experience with SQL, data modeling, cloud data platforms, and ETL tools. Familiarity with Python or other programming languages, orchestration and workflow tools, data quality practices, and platforms such as Snowflake, Amazon Redshift, Google BigQuery, or Microsoft Azure can also be valuable. Many roles call for clear communication and collaboration with analysts, engineers, and business stakeholders.

Find Your Next Data Engineering Opportunity

Data warehouse and ETL roles are available across industries that depend on trustworthy, accessible data. Compare opportunities by seniority, technology stack, work arrangement, and responsibilities. Ladders focuses on vetted professional jobs paying $100,000 or more, helping experienced candidates discover opportunities to advance their careers.

800

Data Warehouse/ETL Developer Jobs

Average Salary: $109,283

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Top companies hiring for Data Warehouse/ETL Developer

Accenture Deloitte TeleTech Infosys Limited Digital CACI International PWC Piper Companies Capgemini Amazon EPAM Systems NTT DATA Services Capital One Financial Corporation Kemper Corporation Geico Avanade Inc.

Top similar job titles to Data Warehouse/ETL Developer

Data Engineer jobs Senior Data Engineer jobs Analytics Engineer jobs Senior Data Analyst jobs Data Analyst jobs Database Engineer jobs Data Architect jobs Senior Software Engineer jobs Integration Engineer jobs Lead Data Scientist jobs Data Science Manager jobs Principal Data Scientist jobs Database Developer jobs Associate IT Consultant jobs Senior Systems Engineer jobs

Top cities hiring for Data Warehouse/ETL Developer

New York, NY jobs Toronto, ON jobs Washington, DC jobs Arlington, VA jobs Dallas, TX jobs Montreal, QC jobs Chicago, IL jobs Mc Lean, VA jobs Chantilly, VA jobs Charlotte, NC jobs

Frequently Asked Questions (FAQ)

What does a Data Warehouse or ETL Developer do?
A Data Warehouse or ETL Developer builds and supports systems that collect data from multiple sources, transform it into useful formats, and load it into warehouses or analytics platforms. They may also develop data models, monitor pipeline quality, and optimize performance.
What skills are commonly required for Data Warehouse and ETL Developer jobs?
Common requirements include SQL, ETL or ELT development, data modeling, and experience with databases or cloud data platforms. Employers may also value Python, workflow orchestration, data quality practices, and communication skills.
Which tools and platforms might appear in job listings?
Depending on the employer, listings may mention Snowflake, Amazon Redshift, Google BigQuery, Microsoft Azure, ETL products, SQL databases, programming languages, and pipeline orchestration tools. Requirements differ by organization and role.
Are Data Warehouse and ETL Developer jobs available for $100,000 or more?
Yes. Ladders features vetted professional jobs paying $100,000 or more, including opportunities in data warehousing and ETL. Compensation and eligibility vary by role, employer, location, and experience.
How can I find the right Data Warehouse or ETL Developer role?
Compare listings based on required technologies, scope of ownership, seniority, industry, and work arrangement. Tailor your resume to highlight relevant pipelines, platforms, data models, and measurable improvements.