# Data Engineer

> Pavago · Pakistan (Remote) · — · Posted 2026-05-06

**Workplace:** remote

**Department:** Candidate Sourcing

## Description

### **🚀 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.

## Apply

[Apply at Pavago](https://apply.workable.com/pavago/j/CF70747EBF/apply)

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