Summary
✨ AI‑Generated
A remote Data Engineer opportunity for someone who enjoys building scalable data infrastructure and dependable ETL/ELT pipelines. You will work across data warehouses, data lakes, data modeling, quality, governance, security, and performance while partnering with analytics and engineering teams to support both real-time and batch workloads.
Highlights
Fully remote role focused on building scalable data infrastructure, reliable pipelines, modern data architectures, and analytics-ready data systems. Offers cross-functional collaboration and exposure to both real-time and batch processing.
Description
This is a remote position.
Job Summary
We are seeking a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data infrastructure and pipelines.
In this role, you will be responsible for ensuring reliable data flow, optimizing data systems, and enabling analytics and business intelligence across the organization.
Key Responsibilities
Design, develop, and maintain scalable data pipelines (ETL/ELT processes)
Build and optimize data architectures, including data warehouses and data lakes
Develop and maintain robust data models to support analytics and reporting
Write efficient SQL queries and manage large datasets
Ensure data quality, integrity, and security across systems
Monitor and troubleshoot data pipeline performance issues
Collaborate with data analysts, data scientists, and software engineers
Implement data governance and best practices
Support real-time and batch data processing solutions
Qualifications
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field
Strong proficiency in SQL and database technologies
Experience with programming languages such as Python, Java, or Scala
Hands-on experience with data pipeline tools (e.g., Apache Airflow, Kafka)
Familiarity with cloud platforms (AWS, Azure, Google Cloud)
Understanding of data warehousing solutions (e.g., Snowflake, Redshift, BigQuery)
Strong problem-solving and analytical skills
Preferred Skills
Experience with big data technologies (e.g., Hadoop, Spark)
Knowledge of data modeling techniques and schema design
Familiarity with containerization tools (Docker, Kubernetes)
Experience with CI/CD pipelines and DevOps practices
Understanding of data security and compliance standards
