Top Hybrid Data Engineering Jobs

The Log Specialist at Dynatrace leads log management initiatives, collaborates with sales, architects data ingestion solutions, and advocates for enhanced log consumption strategies.

The Data Modeler will design and maintain data models, support data architecture, collaborate with product teams, and ensure quality and governance of data products.

As an Analytics Engineer, you will design and manage the data architecture for HR Performance & Goal Management, integrating various data sources and ensuring compliance with data governance standards.

The Senior Data Engineer designs and builds scalable data pipelines, optimizes ETL/ELT workflows, resolves data quality issues, and collaborates with stakeholders for healthcare data integration.

The Data Engineer will develop and manage bioinformatics pipelines, optimize data processing, collaborate with scientists, and enhance data platforms for Pfizer's R&D.

The Data Engineer will build datasets and pipelines for marketing and sales reporting, collaborating with various teams to support data needs and ensure scalable solutions.

The Data Engineer will support data initiatives, build data pipelines, perform statistical analyses, and develop BI dashboards to drive business decisions.

Design and maintain data models in Snowflake to serve as the company's source of truth, ensuring they are clean, queryable, and ready for AI integration. Collaborate with multiple departments to deliver trusted datasets and eliminate inefficiencies in data management.

The Senior Data Engineer will design and optimize large-scale batch and streaming data pipelines using Scala and Spark, oversee the data engineering lifecycle, and engage in technical discussions to improve system efficiency.

Designs, builds, and maintains scalable data pipelines on Databricks, focusing on data quality, integrity, and governance, while collaborating with teams to deliver data solutions.