Data Integration Specialists connect systems, applications, and data sources so organizations can access reliable, usable information. Browse vetted opportunities on Ladders, including roles at established companies seeking professionals to build and maintain data pipelines, support analytics, and improve the flow of business-critical data. Ladders features professional jobs paying $100,000 or more.
These specialists design, develop, and support integrations that move data between databases, cloud services, enterprise applications, and analytics platforms. Responsibilities may include building ETL or ELT workflows, mapping and transforming data, monitoring pipeline performance, resolving integration issues, and documenting processes. Depending on the organization, the role may also involve data quality, security, governance, and collaboration with engineering, analytics, and business teams.
Job requirements vary, but employers commonly look for experience with SQL, data modeling, ETL tools, APIs, and cloud data platforms. Familiarity with Python or another programming language, integration patterns, workflow orchestration, and data warehousing can also be valuable. Strong troubleshooting, communication, and documentation skills help specialists translate business requirements into dependable technical solutions.
Data Integration Specialists can advance into senior integration, data engineering, solution architecture, or data platform leadership roles. Opportunities may be available across industries that depend on connected systems and timely data, including finance, healthcare, technology, retail, and manufacturing. The scope of a role often depends on the size of the organization, its data architecture, and the platforms it uses.
Use Ladders to explore vetted professional opportunities with salaries of $100,000 or more. Review each listing for responsibilities, required technologies, experience expectations, and compensation details, then identify roles that align with your skills and career goals.
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Drive the development of robust data pipelines and architecture to enhance our AI-enabled energy solutions, ensuring reliability and automation while collaborating with product teams to optimize data...
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Pioneer operational excellence in Design leadership, managing workflows, prioritizing projects, and developing talent. Collaborate cross-functionally to enhance Design integration in AI-driven product...
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Lead the charge in database operations, ensuring optimal performance and security for mission-critical systems. Oversee a technical team while aligning with federal standards and integrating with deve...
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What does a Data Integration Specialist do?
A Data Integration Specialist builds and maintains connections between data sources, applications, and platforms. The work often includes developing ETL or ELT pipelines, transforming and validating data, monitoring workflows, and troubleshooting integration problems.
What skills are commonly required for Data Integration Specialist jobs?
Commonly requested skills include SQL, data integration or ETL tools, APIs, data modeling, and cloud or data warehouse platforms. Some employers also seek programming experience, knowledge of orchestration tools, and strong communication and problem-solving abilities.
What is the difference between a Data Integration Specialist and a Data Engineer?
The roles can overlap. Data Integration Specialists often focus on connecting systems and moving or transforming data, while Data Engineers may have broader responsibility for designing and operating data infrastructure and platforms. Duties vary by employer and job title.
How can I find Data Integration Specialist jobs paying $100,000 or more?
Browse Data Integration Specialist listings on Ladders, where professional jobs pay $100,000 or more. Compare the posted responsibilities, qualifications, technologies, and compensation details to find roles that fit your experience.
What career paths can follow a Data Integration Specialist role?
Potential next steps include senior data integration positions, data engineering, data architecture, solutions architecture, or data platform leadership. The best path depends on your experience, technical strengths, and career interests.