Data Integration Engineer

Academian; United States; Remote; USD 100,000 - 160,000; Full time

Benefits offered by this job

Remote work

Job summary

Academian in the United States seeks a Data Integration Engineer to design and maintain data pipelines, ETL/ELT processes, and data integration solutions. You will work with Python, SQL, PySpark, Databricks, Snowflake, and cloud data platforms.

You will integrate data from various sources via APIs, optimize SQL and pipelines, and collaborate with engineering and analytics teams. The role offers a remote work option.

Qualifications

• 3-5 years of experience in data engineering or data integration.
• Strong programming skills in Python and SQL, with PySpark.
• Experience building and managing ETL/ELT pipelines.
• Hands-on with Databricks and Snowflake in cloud environments.
• Familiarity with REST APIs and data transformation workflows.
• Proficiency with Git, CI/CD, and data quality checks.

Responsibilities

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

Skills

Python

SQL

PySpark

ETL/ELT

Data Pipeline Development

Data Integration

Azure/AWS

REST APIs

Git CI/CD

Data Quality Checks

Tools

Databricks

Snowflake

Airflow

Azure Data Factory

Microsoft Fabric

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