Top Hybrid Data Engineering Jobs

The Staff Data Engineer will architect, build, and maintain scalable data pipelines, implement ETL processes, and mentor team members.

Lead technology initiatives for business problems, develop systems and procedures, evaluate challenges, and coordinate communication between teams for CCaaS migrations.

Assist in developing and maintaining data processing pipelines, collaborating with teams to define requirements, and enhancing infrastructure for data sets.

The role involves designing data pipelines, developing metrics and visualizations, collaborating with teams to track product KPIs, and ensuring data integrity within a cybersecurity environment.

As a Senior Associate in data engineering, you'll design data solutions, analyze complex problems, mentor juniors, and build client relationships while navigating challenging projects.

Fora seeks a Senior Analytics Engineer to enhance data modeling and delivery, ensuring access to reliable insights across teams. Responsibilities include managing the analytics layer, improving data performance, and mentoring while collaborating with stakeholders on analytics needs.

Assist in developing, testing, and maintaining software applications, collaborate on designs, participate in code reviews, and contribute to documenting processes.

Develop and implement advanced algorithms, apply statistical techniques, collaborate with clients, assess technologies, and mentor team members.

Work with client and internal teams to design and implement enterprise data solutions. Lead workstreams, translate business problems into technical designs, support delivery activities (architecture, prototypes, test plans, deployment), mentor junior staff, and apply best practices across cloud, data platforms, and visualization tools.

The Data Analytics Engineer will enhance Salesforce analytics, translate business requirements into technical specifications, maintain data flows, and ensure data quality and reporting standards.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.