SENIOR+ DATA ENGINEER - ON-SITE (ATLANTA, USA).

Location: Atlanta, USA. This position requires on-site presence. Candidates currently residing in or willing to relocate to Atlanta are encouraged to apply. Join our dynamic team in a city renowned for its innovation and collaborative spirit.

SKILLS REQUIRED

• At least 7 years of experience in data engineering or related fields, with a strong focus on data architecture and management.
• Proven expertise in SQL and NoSQL databases, such as MySQL, MongoDB, or Cassandra.
• In-depth knowledge of data warehousing solutions like Amazon Redshift, Google BigQuery, or Snowflake.
• Experience with data processing frameworks such as Apache Spark, Apache Kafka, or Hadoop.
• Proficiency in programming languages like Python, Java, or Scala.
• Strong analytical and problem-solving skills, with the ability to work collaboratively in a team environment.
• Excellent communication skills, comfortable engaging with stakeholders at all levels.

PREFERRED QUALIFICATIONS

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Understanding of CI/CD pipelines and automated deployment processes.
• Ability to manage and organize large datasets for machine learning and analytics purposes.

ROLE OVERVIEW

We are searching for a highly experienced and motivated Senior+ Data Engineer to join our expanding team in Atlanta. This on-site role is pivotal in supporting our data infrastructure and ensuring the effective management of large-scale data systems. As a Senior+ Data Engineer, you will work at the forefront of data technology, optimizing data processes and implementing innovative solutions to meet our business objectives.

KEY RESPONSIBILITIES

• Design, develop, and maintain robust data pipelines and architectures.
• Collaborate with cross-functional teams to define data engineering strategies and requirements.
• Implement and optimize ETL processes to ensure seamless data flow and accessibility.
• Ensure data quality and integrity across multiple systems and platforms.
• Analyze and improve existing data frameworks to enhance efficiency and scalability.
• Mentor junior data engineers and promote data-driven best practices within the team.
• Stay updated with the latest trends and technologies in data engineering.