الوصف الوظيفي
🚀 Data Engineer (Python, SQL, ETL, Airflow, Snowflake, BigQuery) Full-Time | Remote | U.
S. Business Hours 💡 About the Role We’re hiring a highly technical Data Engineer to build and maintain scalable data pipelines, cloud data infrastructure, and analytics-ready datasets that power business decision-making.
This role is focused on: ✅ ETL/ELT pipeline development ✅ Data warehouse architecture ✅ SQL optimization ✅ Cloud-based data infrastructure ✅ Pipeline reliability & monitoring ✅ Scalable analytics systems You’ll work closely with: Data Analysts Data Scientists Engineering Teams BI & Leadership Teams to ensure the organization always has accurate, clean, and trustworthy data.
If you: enjoy building robust data systems, love optimizing pipelines and queries, and care deeply about data quality and scalability, this role is a strong fit.
🔥 What You’ll Own ETL / ELT Pipeline Development Build and maintain scalable ETL/ELT pipelines using: Python SQL Scala Ingest data from: APIs SaaS platforms relational databases cloud applications streaming systems Develop reliable workflows for: data extraction transformation loading validation Workflow Orchestration & Automation Manage orchestration platforms such as: Apache Airflow Prefect Dagster Luigi Monitor: pipeline health failed jobs scheduling reliability Build automated workflows with: retries alerting dependency management Data Warehousing & Modeling Design and optimize cloud data warehouses using: Snowflake BigQuery Redshift Develop: star schemas snowflake schemas analytics-ready data models Improve: query performance clustering partitioning warehouse efficiency Data Quality & Governance Implement: validation checks anomaly detection logging systems lineage tracking Use tools such as: dbt Great Expectations Ensure: consistent naming conventions clean transformations audit-ready datasets Support compliance requirements: GDPR HIPAA industry-specific governance standards Streaming & Real-Time Data Build and maintain streaming pipelines using: Kafka Kinesis Pub/Sub Support: real-time ingestion event-driven processing low-latency analytics workflows Infrastructure & DevOps Containerize services using: Docker Kubernetes Build CI/CD workflows with: GitHub Actions Jenkins GitLab CI Manage cloud infrastructure using: Terraform CloudFormation Improve scalability, reliability, and deployment automation Cross-Functional Collaboration Partner with: analysts data scientists BI teams product teams Deliver curated datasets for: dashboards analytics machine learning workflows Support BI tools such as: Tableau Looker Power BI Maintain documentation for: pipelines schemas workflows data definitions ✅ Required Experience & Skills 3+ years of Data Engineering or backend engineering experience Strong proficiency with: Python SQL Experience with: Snowflake BigQuery Redshift Familiarity with: Airflow Prefect workflow orchestration tools Strong understanding of: ETL pipelines data modeling cloud infrastructure warehouse optimization ⭐ Ideal Experience Experience using: dbt Great Expectations data lineage tools Streaming experience with: Kafka Kinesis Pub/Sub Experience with: AWS Glue GCP Dataflow Azure Data Factory Background in: healthcare fintech regulated environments Experience optimizing large-scale warehouse costs and performance 🧠 What Makes You a Great Fit You care deeply about clean and reliable data You enjoy debugging complex pipeline and infrastructure issues You think about scalability and long-term maintainability You combine engineering rigor with analytical thinking You communicate effectively across technical and non-technical teams 📅 What a Typical Day Looks Like Review Airflow/Prefect pipeline health and resolve failures Build connectors for new APIs or SaaS platforms Optimize SQL queries and warehouse performance Collaborate with analysts and data scientists on datasets Improve validation and monitoring systems Document pipelines and warehouse structures Reduce warehouse costs and improve pipeline reliability In short: You build the data infrastructure that powers analytics, reporting, automation, and business intelligence across the organization.
📊 Key Success Metrics (KPIs) Pipeline uptime ≥ 99% Data freshness within SLA Zero critical data quality issues reaching production Query performance & warehouse cost optimization Reliable and scalable pipeline infrastructure Positive feedback from analysts, BI teams, and leadership 🌟 Why This Role Stands Out Work on modern cloud-native data infrastructure Build scalable ETL and analytics systems Exposure to: streaming pipelines cloud data platforms orchestration frameworks warehouse optimization Opportunity to grow into: Senior Data Engineer Analytics Engineering Platform Engineering Data Architecture Fully remote flexibility with collaborative engineering teams 🧪 Interview Process Initial Phone Screen Video Interview with Pavago Recruiter Technical Task (Build a small ETL pipeline or optimize a SQL query) Client Interview with Engineering/Data Team Offer & Background Verification 👉 Apply Now If you: love building scalable data systems, enjoy solving complex pipeline problems, and want to work with modern data infrastructure, this role is a strong fit for you.
لقد تمت ترجمة هذا الإعلان الوظيفي بواسطة الذكاء الاصطناعي وقد يحتوي على بعض الاختلافات أو الأخطاء البسيطة.
