обновлено 2 часа назад
Data Engineer
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer (Python/SQL): Building and maintaining scalable ETL/ELT pipelines, cloud data warehouses, and real-time data systems that power analytics, reporting, and operational decision-making with an accent on data quality, governance, and reliability. Focus on optimizing warehouse performance and cloud costs, monitoring pipeline health, and designing low-latency ingestion and event-driven architectures.
Location: United States; remote work during U.S. client business hours
Company
is coordinating recruitment for a client seeking a Data Engineer to build reliable data infrastructure and pipelines.
What you will do
- Build, maintain, and optimize ETL/ELT pipelines using Python, SQL, or Scala.
- Orchestrate workflows and ingest structured and unstructured data from APIs, SaaS platforms, databases, files, and streaming systems.
- Design and optimize cloud data warehouses, scalable schemas, analytics-ready datasets, and data transformations.
- Implement data validation, anomaly detection, lineage, documentation, monitoring, and audit-ready processes.
- Build and manage real-time pipelines and event-driven architectures using Kafka, Kinesis, Pub/Sub, or similar platforms.
- Collaborate with analysts, data scientists, and business stakeholders while automating deployments and infrastructure.
Requirements
- 3+ years of experience in Data Engineering, Back-End Engineering, or Data Infrastructure roles.
- Strong proficiency in Python and SQL.
- Experience with Snowflake, Redshift, or BigQuery and with Airflow, Prefect, or similar orchestration tools.
- Strong understanding of ETL/ELT pipelines, data modeling, and transformation workflows.
- Familiarity with AWS, GCP, or Azure.
- Ability to work U.S. client business hours, with flexibility for pipeline monitoring, deployments, and data refresh cycles.
Nice to have
- Experience with dbt, Kafka, Kinesis, Pub/Sub, AWS Glue, GCP Dataflow, or Azure Data Factory.
- Familiarity with Docker, Kubernetes, Terraform, or CI/CD workflows.
- Background in healthcare, fintech, or enterprise SaaS.
- Experience optimizing warehouse costs and query performance at scale.
Culture & Benefits
- Remote full-time position.
- Ownership of data quality, pipeline reliability, and technical documentation.
- Cross-functional collaboration with technical and non-technical stakeholders.
- Success is measured by pipeline uptime, data freshness, data quality, warehouse performance, and reliable dataset delivery.
Hiring process
- Initial phone screen.
- Video interview with a recruiter and client interview with the engineering/data team.
- Technical assessment, offer, and background verification.
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