Data Engineer Jobs with Salary ≥ 100k

Summary: Candidates should have over 10 years of experience in data engineering or AI platforms, with at least 5 years in a senior or principal-level role. A strong background in production operations and the ability to lead complex technical initiatives is essential.

Skills: snowflake, cloud platforms, llm platforms, rag architectures, modern data stacks, ai/ml platforms, infrastructure as code, ci/cd pipelines, observability, incident management, reliability engineering

Summary: Candidates should have strong software engineering fundamentals and experience in building frameworks for data platforms. A broad understanding of cloud architecture tools and significant experience with Big Data and data lakes is essential.

Skills: software engineering fundamentals, data platforms, cloud architecture, big data, spark, sql, etl testing, ci/cd tools, scala, java, python, aws, distributed systems, automation, data pipeline orchestration, debugging, performance tuning

Summary: Candidates should have at least 10 years of experience in software or data engineering, with a focus on data pipelines. Proven experience in driving technical direction and mentoring engineers is essential.

Skills: java, microservices, data pipelines, apache hudi, apache trino, azure adls, event-driven architectures, cloud platforms, ci/cd integration, data quality practices, observability, data governance, lakehouse architectures, big data technologies, collaboration, communication

Summary: Candidates should have at least 10 years of experience in software or data engineering, with a focus on data pipelines. Proven experience in driving technical direction and mentoring engineers is essential.

Skills: java, microservices, data pipelines, cloud platforms, event-driven architectures, data quality practices, ci/cd integration, observability, data governance, performance optimization, lakehouse architectures, apache hudi, azure adls gen2, hdfs, trino, databricks

Summary: Candidates should have a Bachelor's degree in Computer Science or a related field, with 5+ years of experience in backend and API development. They must also have hands-on experience with Gravitee API Management Platform and designing ETL processes.

Skills: api development, api management, gravitee, identity management, etl processes, data engineering, backend engineering, restful apis, graphql, oauth 2.0, scim, java, python, node.js, database technologies, data pipeline tools

Summary: Data Engineer to build scalable data pipelines and analytics-ready warehousing on GCP; must be strong in Python and SQL; experience with Temporal, Airflow, or Dagster.

Skills: python, sql, temporal, airflow, dagster, go, typescript, next.js, postgresql, bigquery, bigtable, cloud-run, gcp

Summary: Candidates should have expertise in architecting large-scale data solutions and integrating AI and ML into data environments. A strong background in data governance and security frameworks is also required, along with excellent leadership and communication skills.

Skills: data engineering, data governance, artificial intelligence, machine learning, cloud platforms, big data, data architecture, data strategy, compliance, security frameworks, leadership, communication, software engineering, mentoring, automation, predictive analytics