Informatica Lead

TechDigital Group; Charlotte (NC); On-site; USD 80,000 - 110,000; Full time

Job summary

An innovative firm is seeking a skilled Data Engineer to design and implement robust data pipelines. In this role, you will be responsible for extracting, transforming, and loading data into a data warehouse while optimizing data storage systems for performance. You will collaborate with data scientists to deploy machine learning models and ensure data governance policies are upheld. This position offers the opportunity to mentor junior team members and contribute to cutting-edge data engineering practices in a dynamic environment. If you are passionate about data and eager to make an impact, this role is perfect for you.

Qualifications

• Proficiency in data engineering tools and methodologies.
• Strong background in SQL and data modeling.

Responsibilities

• Design and implement data pipelines for ETL processes.
• Collaborate with data scientists to deploy machine learning models.
• Mentor junior engineers on best practices in data engineering.

Skills

Informatica Power Center

Unix

Oracle

strong SQL

Python

Job description

Minimum Mandatory Skills: Informatica Power Center, Unix, Oracle / strong SQL, Python

Responsibilities:

1. Design and implement data pipelines to extract, transform, and load data from various sources into a data warehouse.
2. Develop and maintain data models and schemas to support business intelligence and analytics applications.
3. Optimize data storage and retrieval systems for performance and scalability.
4. Collaborate with data scientists and analysts to develop and deploy machine learning models and algorithms.
5. Implement data governance policies and procedures to ensure data quality, security, and compliance.
6. Develop and maintain ETL workflows using tools.
7. Design and implement data integration solutions for third-party applications and services.
8. Conduct performance tuning and optimization of database systems and queries.
9. Mentor and train junior data engineers and other team members on best practices and emerging technologies in data engineering.
10. Building and managing DevOps & DataOps CI/CD pipelines and automated deployments.
11. Prepare technical design documents and SLA agreements.