Data Integration Engineer

VettedBench; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

VettedBench is seeking a Data Integration Engineer to design and optimize data pipelines, ETL/ELT processes, and data integration solutions. The ideal candidate will have hands-on experience with Python, SQL, PySpark, Databricks, and Snowflake, plus cloud data platform exposure.

This remote role targets professionals with 3–5 years in data engineering or data integration. You will build and maintain data pipelines, integrate data from multiple sources, and ensure data quality and performance

Qualifications

• 3–5 years of data engineering or data integration experience.
• Hands-on with Python, SQL, PySpark and data transformation.
• Experience building data pipelines and ETL/ELT in cloud environments.

Responsibilities

• Develop and maintain ETL/ELT pipelines and data ingestion processes.
• Work with Python, SQL, PySpark, and Databricks for data transformation.
• Integrate data from multiple sources using databases and REST APIs.
• Work with Snowflake, Azure, AWS and Microsoft Fabric.
• Implement data quality checks, validation and reconciliation processes.
• Optimize data pipelines and SQL queries for performance.
• Collaborate with engineering and analytics teams.

Skills

Python

SQL

PySpark

ETL/ELT

Data pipelines

Data warehousing

Azure/AWS

Airflow/Data Factory

REST APIs

Git/CI/CD

Data quality

Tools

Databricks

Snowflake

Job description

**Experience:** 3–5 Years

**Employment Type:** Contract / Full-Time

Job Summary

We are looking for a Data Integration Engineer with hands‑on experience in developing data pipelines, ETL/ELT processes, and data integration solutions. The ideal candidate should have strong expertise in Python, SQL, PySpark, Databricks, and Snowflake, along with cloud data platform experience.

Key Responsibilities

• Develop and maintain ETL/ELT pipelines and data ingestion processes.
• Work with Python, SQL, PySpark, and Databricks for data transformation.
• Integrate data from multiple sources using databases and REST APIs.
• Work on Snowflake, Azure, AWS, and Microsoft Fabric.
• Implement data quality checks, validation, and reconciliation processes.
• Optimize data pipelines and SQL queries for better performance.
• Collaborate with engineering and analytics teams.

Required Skills

• Python, SQL, PySpark
• Databricks and Snowflake
• ETL/ELT and Data Pipeline Development
• Data Integration and Data Warehousing
• Azure and/or AWS
• Apache Airflow / Azure Data Factory
• REST APIs and Data Transformation
• Git, CI/CD, and Data Quality Checks

Good to Have

• Microsoft Fabric, Salesforce, Power BI
• Terraform and AI/RAG exposure
• Experience with large‑scale datasets.

Ideal Candidate

Candidates with 3–5 years of experience in Data Engineering or Data Integration, strong programming skills, and practical experience in building and managing data pipelines.

Work Location: Remote