Remote Big Data Engineer (The Data Pipeline Innovator)

Description:

• The Big Data Engineer will handle massive datasets and build infrastructure for complex data analysis and machine learning at scale.
• This role involves creating robust, scalable data pipelines that support data-driven decision-making.
• The engineer will collaborate with data scientists, analysts, and software engineers to design, implement, and optimize big data platforms.
• Key responsibilities include architecting and implementing data pipelines for ETL processes using tools like Apache Spark, Kafka, and Hadoop.
• The engineer will develop and manage data storage solutions optimized for performance and cost-efficiency.
• Collaboration on data strategy and integration is essential to align big data architecture with analytics goals.
• The role requires implementing data quality and governance standards to ensure data accuracy and reliability.
• Automation of data workflows using tools like Apache Airflow or AWS Glue is a key responsibility.
• Monitoring and troubleshooting data systems to maintain optimal processing capabilities is required.
• Staying updated on big data trends and technologies to integrate new techniques that promote innovation is expected.

Requirements:

• Extensive experience with big data technologies such as Apache Spark, Hadoop, Kafka, and Hive is required.
• Proven ability to design, build, and maintain ETL processes for massive datasets is essential.
• Proficiency in programming languages like Python, Java, or Scala, along with SQL for data querying, is necessary.
• Familiarity with cloud platforms such as AWS, GCP, or Azure, including their big data and storage services, is required.
• A strong understanding of data quality standards and governance practices is essential.
• A Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, or a related field is required.
• Certifications in big data or cloud technologies are a plus.
• A minimum of 5 years of experience in data engineering, with at least 3 years focusing on big data technologies, is required.
• Experience in distributed systems and large-scale data storage management is necessary.
• Familiarity with containerization technologies like Docker and Kubernetes is advantageous.

Benefits:

• Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums are provided.
• Competitive vacation, sick leave, and 20 paid holidays per year are offered.
• Flexible work schedules and telecommuting options promote work-life balance.
• Opportunities for training, certification reimbursement, and career advancement programs are available.
• Access to wellness programs, including gym memberships, health screenings, and mental health resources, is provided.
• Life insurance and short-term/long-term disability coverage are included.
• Confidential counseling and support services through an Employee Assistance Program (EAP) are available.
• Financial assistance for continuing education and professional development through tuition reimbursement is offered.
• Opportunities to participate in community service and volunteer activities are encouraged.
• Employee recognition programs celebrate achievements and milestones.