Senior Data Architect - Remote, AI/ML Upskill Path

Inorg Global; Indiana (PA); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote work opportunities

Flexible hours

Job summary

Inorg Global is seeking an experienced Data Architect to design and operate large-scale data systems. The role emphasizes Python, SQL, ETL, and data modeling, with hands-on use of Teradata, Informatica, Hadoop, Spark, PySpark, ADF, Snowflake, and Kafka.

Cloud knowledge (AWS/Azure/GCP) is a plus, with an opportunity to transition into Databricks and AI/ML projects. The ideal candidate will work across cross-functional teams, building scalable data pipelines, optimizing data platforms, and

Qualifications

• Relevant experience in data engineering.
• Strong proficiency in Python, SQL, ETL, and data modeling.
• Experience with Teradata, Informatica, Hadoop, Spark, PySpark, ADF, Snowflake, Big Data, Scala, Kafka.
• Cloud knowledge (AWS, Azure, or GCP) is a plus.
• Willingness to learn and adapt to new technologies, specifically Databricks & AI/ML.

Responsibilities

• Design, develop, and maintain large-scale data systems.
• Develop and implement ETL processes using various tools and technologies.
• Collaborate with cross-functional teams to design and implement data models.
• Work with big data tools like Hadoop, Spark, PySpark, and Kafka.
• Develop scalable and efficient data pipelines.
• Troubleshoot data-related issues and optimize data systems.
• Transition and upskill into Databricks & AI/ML projects.

Skills

Python

SQL

ETL

Data modeling

Cloud knowledge

Willingness to learn

Tools

Teradata

Informatica

Hadoop

Spark

PySpark

ADF

Snowflake

Kafka

Scala

Job description

Inorg Global is seeking an experienced Data Architect to design and operate large-scale data systems. The role emphasizes Python, SQL, ETL, and data modeling, with hands-on use of Teradata, Informatica, Hadoop, Spark, PySpark, ADF, Snowflake, and Kafka.

Cloud knowledge (AWS/Azure/GCP) is a plus, with an opportunity to transition into Databricks and AI/ML projects. The ideal candidate will work across cross-functional teams, building scalable data pipelines, optimizing data platforms, and