Data Engineer

VORKIS; New Braunfels (TX); On-site; USD 153,142 - 204,708; Full time

Job summary

VORKIS is seeking a skilled Middle Data Engineer to design and maintain data infrastructure and pipelines. The ideal candidate will optimize data processes and ensure smooth data flow to support decision-making.

Key qualifications include 3+ years in data engineering, experience with cloud platforms, and proficiency in programming languages like Python and SQL. Join us in our innovative environment!

Qualifications

• B2+ English level.
• 3+ years of experience in data engineering or a related role.

Responsibilities

• Design and implement effective data architecture solutions.
• Build efficient ETL processes to extract, transform, and load data.
• Ensure data security and privacy.
• Implement optimizations to improve data processing performance.

Skills

JAVA

Azure

Machine Learning

Information Security

Pipeline

AWS

Reporting Tools

BI

Data Warehousing

Python

Automated Testing

Data Pipelines

Databases

ETL

Big Data

Spark

Agile

SQL

Data Engineering

Communication Skills

Education

Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering

Job description

Job Summary

We are an innovative company looking for a skilled Middle Data Engineer to join our dynamic team. Our collaborative culture fosters creativity and leverages the latest technologies. As a key member of our team, you will design, build, and maintain the data infrastructure and pipelines necessary for efficient and reliable data processing. You will ensure the smooth flow of data from various sources to the desired destinations, enabling data-driven decision-making across the organization. If you are passionate about data and have a knack for optimizing data processes, we would love to hear from you.

Salary

Salary: $153,142 - $204,708 per year

Location

Location: TX, New Braunfels, US, 78132

Employment Option

Employment option: Full time

Job Type

Job type: Full time

Skills

Must Have Hard skills:

• novice in: JAVA, Azure, Machine Learning, Information Security
• beginner in: Pipeline, AWS, Reporting Tools, BI, Data Warehousing
• competent in: Python

Nice-to-have Hard skills:

• novice in: Automated Testing
• beginner in: Data Pipelines, Databases, ETL, Big Data, Spark, Agile
• competent in: SQL, Data Engineering

Soft skills:

• competent in: Communication Skills

Additional Requirements

Qualification

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• B2+ English level

Experience

• Experience with data warehousing concepts and technologies, such as Amazon Redshift or Google BigQuery.
• Experience with cloud platforms like Amazon Web Services (AWS) or Azure, and their data engineering services.
• 3+ years of experience in data engineering or a related role.
• Experience with data integration and ETL tools.
• Experience with big data technologies such as Hadoop and Spark.

Requirements

• Proficiency in designing and developing ETL processes and data integration solutions using tools like Apache Spark or Python libraries such as pandas.
• Strong knowledge of relational databases and SQL for data manipulation, query optimization, and performance tuning.
• Proficiency in programming languages commonly used in data engineering, such as Python or Java.
• Understanding of machine learning and data science concepts.
• Understanding of data security and privacy best practices.
• Familiarity with data pipeline orchestration tools.
• Strong analytical and problem-solving skills to identify and resolve data engineering challenges.Effective communication skills and the ability to collaborate with cross‑functional teams to understand requirements and deliver data solutions.

Responsibilities

• Collaborate with stakeholders to design and implement effective data architecture solutions that meet business requirements and support scalability.
• Build efficient and robust Extract, Transform, Load (ETL) processes to extract data from various sources, transform it into a usable format, and load it into data warehouses or data lakes.
• Ensure data security and privacy.
• Design and develop data pipelines to facilitate the seamless flow of data between systems, ensuring data availability and integrity.
• Implement data quality checks and validation processes to ensure data accuracy, consistency, and integrity.
• Identify and implementing optimizations to improve data processing performance.
• Document data engineering processes, data flows, and system architecture.
• Stay up-to-date with the latest data engineering trends and technologies.

About Company

7‑Eleven, Inc. is a leading convenience‑retailing company based in Irving, Texas, operating and franchising thousands of stores across the U.S. and Canada.