Data Engineer
- USA
- $55.00 per hour
- Permanent
- Full-time
Rate: $55/hr.
Remote
11 MonthsAbout the RoleWe are seeking skilled and motivated Data Engineers to join our growing team. This role is ideal for professionals who have a strong foundation in data engineering and a proven track record of working with modern data technologies including Databricks, Spark, PySpark, DataOps, Python, and SQL. You will be instrumental in designing, building, and maintaining scalable data pipelines and data processing systems that support analytics and business operations.Key Responsibilities
Design, develop, and maintain scalable and efficient data pipelines using Spark and PySpark within the Databricks ecosystem.
Collaborate with Data Scientists, Analysts, and Business Stakeholders to understand data needs and deliver data solutions that are robust and efficient.
Implement and manage DataOps practices to streamline data development and deployment processes.
Ensure data quality and governance through rigorous testing, validation, and monitoring of data pipelines.
Develop ETL/ELT workflows and scripts using Python and SQL.
Monitor performance and troubleshoot issues in large-scale distributed systems.
Contribute to architectural decisions and performance optimization strategies.
Document technical designs, operational procedures, and data workflows.Required Skills & Qualifications
Minimum 3 years of experience in a Data Engineering role.
Hands-on experience with Databricks, including Delta Lake and MLflow is preferred.
Strong expertise in Apache Spark and PySpark.
Solid proficiency in Python programming for data processing tasks.
Advanced SQL skills with the ability to write complex queries and optimize them for performance.
Practical knowledge of DataOps principles, tools, and automation.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with version control tools (e.g., Git) and CI/CD pipelines.
Strong analytical and problem-solving skills.
Excellent verbal and written communication skills.Preferred QualificationsExperience with real-time data processing frameworks such as Kafka or Flink.
Familiarity with orchestration tools like Airflow, Dagster, or Prefect.
Knowledge of data security, privacy, and compliance best practices.
Exposure to machine learning model deployment and monitoring workflows.Why Join Us
Work with cutting-edge technologies in a fast-paced, collaborative environment.
Opportunity to solve complex data problems that have real business impact.
Flexible work arrangements and a supportive team culture.