Data Engineer

As a Data Engineer, you will play a critical role in designing and maintaining robust data pipelines that power high-impact business products. You will work within a modern cloud-based ecosystem to optimize data delivery, ensure data quality, and implement automation across the entire data lifecycle. This role offers the opportunity to work with distributed systems and advanced analytics platforms in a hybrid work environment.

We are representing a leading global computer software company known for its innovative data-driven solutions. The organization fosters a collaborative, fast-paced environment that prioritizes technical excellence and scalable engineering practices. They are committed to leveraging cutting-edge cloud technologies to solve complex business challenges on a global scale.

Responsibilities

• Design and implement scalable data pipelines to integrate with internal products and external vendor systems.
• Develop and maintain automation processes to optimize data delivery and reduce cloud infrastructure costs.
• Implement comprehensive systems for data quality monitoring, observability, governance, and lineage.
• Manage production environments, including troubleshooting issues and performing root cause analysis.
• Write high-quality unit and integration tests while adhering to test-driven development principles.
• Collaborate with cross-functional teams to document design specifications and engineering best practices.
• Utilize modern data platforms such as Databricks and Snowflake to support complex analytical requirements.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 5-8 years of professional experience in data engineering or a related technical role.
• Strong proficiency in Python with a focus on production-quality data pipeline development.
• Hands-on experience with big data technologies including Hadoop, Spark, Hive, and SQL.
• Proven expertise in workflow orchestration tools such as Airflow or Dagster.
• Solid experience working with cloud platforms, specifically AWS.
• Proficiency in Git, JIRA, Jenkins, and shell scripting.
• Experience building data pipelines for digital marketing use cases is highly desirable.

Skills

Python, Hadoop, Spark, SQL, Airflow, Dagster, AWS, Big Data, Databricks, Snowflake, Hive, Git, JIRA, Jenkins, Shell Scripting, Digital Marketing data pipelines