Data Engineer

Description:

Job Title: Data Engineer (Hybrid)
Location: Texas (Hybrid - 2-3 days in office per week)
Experience: 2-5 years

Company Overview:
We are a fast-growing tech company looking for a talented Data Engineer to join our dynamic team in Texas. If you have a passion for data and technology, and want to work on exciting projects with cutting-edge tools and technologies, this is the role for you. This hybrid position offers flexibility with a mix of in-office and remote work, providing a great work-life balance.

Job Summary:
As a Data Engineer, you will be responsible for designing, developing, and maintaining data pipelines that enable efficient data processing and analytics. You will work closely with data scientists, analysts, and other engineering teams to ensure data is reliable, accessible, and optimized for analysis.

Key Responsibilities:
Develop and maintain scalable and efficient ETL (Extract, Transform, Load) pipelines to process large datasets.
Design and implement data models and architectures for data storage and analysis.
Collaborate with cross-functional teams to identify data requirements and ensure data solutions meet business needs.
Optimize and troubleshoot data processing workflows for performance and reliability.
Ensure data quality and integrity across various systems.
Work with cloud platforms (AWS, Azure, GCP) to deploy data solutions and manage cloud-based data storage.
Automate manual data tasks and processes to increase efficiency.
Monitor and ensure compliance with data security and privacy regulations.
Document data processes, architectures, and workflows.
Required Skills & Experience:
2-5 years of experience as a Data Engineer, Data Analyst, or similar technical role.
Strong proficiency in SQL and Python for data manipulation and analysis.
Experience with data warehousing technologies (e.g., Snowflake, Redshift, BigQuery, etc.).
Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience with ETL tools and data pipeline frameworks.
Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.
Solid understanding of data modeling, database design, and data warehousing principles.
Excellent problem-solving skills, attention to detail, and ability to troubleshoot data-related issues.
Strong communication skills and the ability to collaborate with various teams.

Preferred Qualifications:
Experience with machine learning or advanced analytics.
Knowledge of data governance and data privacy best practices.
Familiarity with version control systems like Git.

Why You Should Apply:
Competitive salary and comprehensive benefits package.
Hybrid work schedule offering flexibility.
Opportunity to work with cutting-edge technologies in a growing company.
Career growth opportunities and a supportive work environment.