Fusemachines is a 10+ year old AI company focused on delivering advanced AI products and solutions across various industries.
The company is dedicated to democratizing AI and leveraging global AI talent from underserved communities.
This is a remote full-time contractual position in the Travel & Hospitality Industry.
The role involves designing, building, testing, optimizing, and maintaining infrastructure and code for data integration, storage, processing, pipelines, and analytics.
Responsibilities include implementing data flow controls and ensuring high data quality and accessibility for analytics and business intelligence.
The ideal candidate should have a strong foundation in programming and effective data management across various storage systems and technologies.
The position requires a skilled Sr. Data Engineer with expertise in Python, SQL, PySpark, Redshift, and AWS cloud-based data solutions.
The candidate should be able to work independently and mentor junior team members with minimal oversight.
The role is suited for someone passionate about using data to drive insights and support organizational goals through innovative data engineering solutions.
Requirements:
A full-time Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field is required.
A minimum of 5 years of real-world data engineering experience in AWS is necessary, with certifications preferred.
Strong expertise in Python, SQL, PySpark, and AWS in an Agile environment is essential, along with a proven track record in building and optimizing data pipelines and architectures.
The candidate must be able to understand requirements and design end-to-end solutions with minimal oversight.
Proficiency in programming languages such as Python or Scala and writing optimized code for data integration and processing is required.
Knowledge of SDLC tools and technologies, including project management software (Jira), source code management (GitHub), and CI/CD systems is necessary.
A good understanding of Data Modelling and Database Design Principles is required to design efficient database schemas.
Strong SQL skills and experience with complex data sets, Enterprise Data Warehouse, and advanced SQL queries are essential.
Experience in data integration from various sources, including APIs and databases, is required.
The candidate should have strong experience in implementing data pipelines and ELT/ETL processes in AWS.
Familiarity with scalable and distributed Data Technologies such as Spark/PySpark, DBT, and Kafka is necessary.
Experience in designing and implementing Data Warehousing solutions in AWS with Redshift is required.
Knowledge of orchestration using Apache Airflow is essential.
Expertise in AWS cloud computing services, including Lambda, Kinesis, S3, and others, is necessary.
Understanding of Data Quality and Governance, including data quality checks, is required.
Familiarity with BI solutions, including Looker and LookML, is a plus.
Strong knowledge of DevOps principles and tools, including CI/CD and infrastructure as code, is necessary.
Good problem-solving skills and the ability to troubleshoot data processing pipelines are required.
Strong leadership, project management, and organizational skills are essential.
Excellent communication skills to collaborate with cross-functional teams are necessary.
The ability to document processes and configurations is required.
Benefits:
The position offers the opportunity to work remotely, providing flexibility in work location.
Employees will be part of a diverse and inclusive work environment committed to equal opportunity.
The role allows for professional growth and the chance to work with cutting-edge technologies in the AI field.
Employees will have the opportunity to mentor and guide junior team members, enhancing leadership skills.
The company fosters a culture of continuous learning and improvement, encouraging employees to expand their skills in data engineering and cloud platforms.
