Data Engineer

Overview:

Are you a data enthusiast who thrives on building scalable and efficient data pipelines? Do you have a passion for transforming raw data into actionable insights? If so, we want you to join our fast-growing startup and help shape the future of data-driven retail!

Who We Are:

We're a small but ambitious startup revolutionizing the retail experience through innovative technology. We're passionate about creating user-friendly, engaging experiences that make shopping effortless and enjoyable. We work collaboratively, value open communication, and believe in fostering a culture of continuous learning and growth.

What You'll Do:
Design, build, and maintain scalable data pipelines and ETL processes to support business analytics and operational needs.
Collaborate with cross-functional teams to integrate, transform, and make data accessible for analysis and decision-making.
Implement and optimize data ingestion processes, ensuring efficient data movement across systems.
Develop and manage Spark-based data processing workflows for real-time and batch processing.
Write clean, efficient, and well-documented Python code to support data engineering workflows.
Monitor and troubleshoot data pipelines, ensuring high availability and reliability.
Drive best practices for data governance, security, and quality to ensure accuracy and consistency.
Stay up to date with industry trends, tools, and best practices to continuously improve our data architecture and processes
Mentor team members or lead projects if interested in growing into a leadership role.
What You Bring:
3+ years of experience as a Data Engineer, working with large-scale data infrastructure.
Strong proficiency in Python for data processing and automation.
Deep understanding of distributed data processing architecture and tools such as Spark, Kubernetes and Kafka.
Experience working with data integration tools.
Deep understanding of ETL processes and data pipeline orchestration.
Self-motivated and proactive with a strong ability to learn new technologies quickly.
A humble yet confident mindset, open to feedback and collaboration.
Excellent problem-solving skills with a keen attention to detail.
Bonus Points:
Experience with cloud platforms such as GCP, AWS, or Azure.
Familiarity with data warehouse solutions like Snowflake, BigQuery, or Redshift.
Knowledge of workflow orchestration tools such as Apache Airflow.
Experienced in deploying and maintaining complex machine learning models in production environments.
Prior experience working in a startup environment.
Knowledge of CI/CD pipelines and test-driven development.