Pavago
Staffing and Recruiting
DataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer at Pavago. Skills: Data Pipelines, Data Warehousing, Cloud Platforms, ETL/ELT. Build ETL/ELT pipelines. Orchestrate workflows”
What You'll Achieve.
Pipeline uptime ≥ 99%; Data freshness within SLAs; Zero critical data quality issues; Improved warehouse query performance; Cost optimization; Timely delivery of datasets; Positive stakeholder feedback
Industry & Context.
Debugging; Problem-solving mindset; Analytical thinking
What They're Looking For.
Must Have
Python, SQL, Snowflake, Redshift, BigQuery, Airflow, Prefect, ETL/ELT pipelines, Data modeling, Data transformation workflows, AWS, GCP, Azure
Nice to Have
dbt, Kafka, Kinesis, Pub/Sub, AWS Glue, GCP Dataflow, Azure Data Factory, Docker, Kubernetes, Terraform, CI/CD workflows, healthcare, fintech, enterprise SaaS, warehouse costs, query performance
What You'll Do.
Build ETL/ELT pipelines
Orchestrate workflows
Ingest structured data
Ingest unstructured data
Develop scalable connectors
Manage cloud data warehouses
Design scalable schemas
Implement partitioning
Build analytics-ready datasets
Implement validation checks
Implement anomaly detection
Enforce naming conventions
Enforce lineage tracking
Enforce documentation standards
Maintain audit-ready data processes
Ensure GDPR compliance
Ensure HIPAA compliance
Monitor pipeline health
Resolve inconsistencies
Build real-time data pipelines
Manage streaming infrastructure
Partner with analysts
Partner with data scientists
Partner with business stakeholders
Support dashboard initiatives
Support reporting initiatives
Translate business requirements
Containerize data services
Manage cloud infrastructure
How You'll Work.
Team & Collaboration
Work across engineering, analytics, and business teams; Partner closely with analysts, data scientists, and business stakeholders; Collaborate with analysts and data scientists
Communication Scope
Proactive communicator
Full Job Description
### **Job Title: Data Engineer** **Position Type:** Full-Time, Remote **Working Hours:** U.S. client business hours (with flexibility for pipeline monitoring, deployments, and data refresh cycles) ### **About the Role** Our client is seeking a Data Engineer to design, build, and maintain scalable data infrastructure and reliable data pipelines that power analytics, reporting, and operational decision-making across the business. This role requires strong software engineering fundamentals, deep experience with modern data stacks, and a passion for building clean, reliable, and high-performance data systems. The Data Engineer will ensure data flows seamlessly from source systems into warehouses, dashboards, and downstream applications while maintaining high standards for quality, governance, and scalability. The ideal candidate is analytical, detail-oriented, and comfortable working across engineering, analytics, and business teams to deliver trustworthy and actionable data. ### **Responsibilities** ### **Pipeline Development & Data Integration** • Build, maintain, and optimize ETL/ELT pipelines using Python, SQL, or Scala • Orchestrate workflows using Airflow, Prefect, Dagster, or similar orchestration tools • Ingest structured and unstructured data from APIs, SaaS platforms, databases, files, and streaming systems • Develop scalable connectors and automated ingestion workflows ### **Data Warehousing & Modeling** • Manage and optimize cloud data warehouses such as Snowflake, BigQuery, or Redshift • Design scalable schemas using star and snowflake modeling techniques • Implement partitioning, clustering, indexing, and performance optimization strategies • Build clean, analytics-ready datasets for business intelligence and reporting use cases ### **Data Quality, Governance & Reliability** • Implement validation checks, anomaly detection, logging, and monitoring to ensure data integrity • Enforce naming conventions, lineage tracking, and documentation standards using too
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