Staff Software Engineer, Data Platform
New
J
JobgetherData infrastructure
Workplace type: Remote; based in United States.Full-TimeStaff
SalaryBase compensation range of $200,000–$260,000
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Job Details
- Experience
- At least 8 years of experience in Data Platform engineering or an equivalent combination of professional and academic experience in a quantitative field
- Required Skills
- ETLGCPKafkaAirflowSparkBigQuerydbtDatabricks
Requirements
- Bring at least 8 years of experience in Data Platform engineering or equivalent professional and academic experience in a quantitative field.
- Have experience leading company-wide technical initiatives across multiple teams and influencing technology roadmap planning.
- Collaborate with technical and business stakeholders to deliver tangible outcomes.
- Balance execution and operational delivery with technical research, statistical understanding, and scalable system design.
- Have significant technical leadership experience with ETL frameworks, metrics stores, infrastructure, data security, and large-scale data processing.
- Have experience building, deploying, and maintaining reliable data pipelines across multiple geographic environments and at scale.
- Have familiarity with workflow and orchestration technologies such as Airflow and dbt.
- Have hands-on experience designing modern Lakehouse data processing patterns.
- Bring experience with big data and cloud technologies such as GCP, Databricks, BigQuery, DataProc, Kafka, Kubernetes, Spark, DataFlow, Google Cloud Storage, and Airflow; experience across the full set is not required.
- Evaluate technologies, conduct proofs of concept, and use findings to inform architecture and platform decisions.
- Have experience mentoring engineers, scientists, and peers.
Responsibilities
- Provide technical leadership for the strategy, architecture, development, deployment, and operation of large-scale data and AI platforms.
- Identify and solve organization-wide technical challenges through scalable and reliable data platform solutions.
- Establish architectural direction and technical standards while remaining hands-on with engineering and platform problems.
- Lead cross-team initiatives, influence technology roadmaps, and translate technical strategy into business outcomes.
- Drive best practices across data engineering and platform development.
- Provide technical leadership across ETL frameworks, metrics stores, infrastructure management, data security, and scalable data processing systems.
- Design, build, deploy, and maintain reliable multi-geographical data pipelines at scale.
- Contribute to Lakehouse architecture patterns and reusable platform components, services, and client libraries for big data workloads.
- Evaluate emerging technologies, conduct proofs of concept, and guide architecture decisions through research and technical analysis.
- Mentor engineers, scientists, and technical peers and collaborate with teams, stakeholders, leadership, and platform users.
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