Job Title: Big Data Engineer Location: Remote
Job Type: Contract
Department: [Data Engineering/IT/Analytics]
Reports To: [Data Engineering Manager/CTO]
Job Summary: We are looking for a skilled Big Data Engineer to design, build, and maintain scalable data pipelines and infrastructure.
The ideal candidate will have experience working with large datasets, distributed systems, and modern data processing frameworks.
You will play a key role in enabling data-driven decision-making across the organization.
Key Responsibilities:
- Design and implement robust, scalable data pipelines using tools like Apache Spark, Hadoop, Kafka, and Flink.
- Develop ETL processes to ingest, transform, and store structured and unstructured data.
- Optimize data workflows for performance, reliability, and scalability.
- Collaborate with data scientists, analysts, and software engineers to support data needs.
- Ensure data quality, governance, and security across platforms.
- Monitor and troubleshoot data pipeline issues and system performance.
- Stay current with emerging big data technologies and best practices.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- 3+ years of experience in big data engineering or related roles.
- Proficiency in distributed data processing frameworks (e.g., Spark, Hadoop, Hive).
- Strong programming skills in Python, Java, or Scala.
- Experience with cloud platforms (AWS, Azure, GCP) and data services.
- Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
- Knowledge of SQL and NoSQL databases.
Preferred Qualifications:
- Experience with real-time data processing using Kafka, Flink, or similar tools.
- Understanding of data lake and data mesh architectures.
- Exposure to containerization and orchestration tools (Docker, Kubernetes).
- Certifications in cloud or big data technologies.
Benefits:
- Competitive salary and performance incentives.
- Health, dental, and vision insurance.
- Flexible work hours and remote work options.
- Opportunities for professional development and training.