Note: The job is a remote job and is open to candidates in USA. Noctua Technology is a company focused on data-driven operations, seeking a talented and motivated Senior Data Engineer to join their dynamic Data Engineering team. The role involves constructing and optimizing data pipelines, implementing storage solutions, and leading engineering engagements to support customer data initiatives.

Responsibilities

• Acquire, clean, and preprocess diverse datasets from various sources, establishing best practices and ensuring data quality standards
• Design and build required infrastructure for optimal extraction, transformation and loading of data from various data sources using CSP managed services and SQL technologies, focusing on scalability and cost efficiency
• Develop, maintain, and optimize mission-critical data pipelines to ensure a continuous flow of high-quality data, implementing robust monitoring and alerting
• Architect and develop data migration strategies and schemas to lead complex customer migrations from on-prem to cloud technologies
• Oversee and execute high-volume data migration activities, ensuring data integrity and minimal downtime
• Optimize databases and data warehouses for efficient querying and data storage, implementing advanced partitioning, indexing, and tuning techniques
• Perform exploratory data analysis to uncover patterns, trends, and insights, providing actionable recommendations to technical and business stakeholders
• Create visualizations and reports to communicate findings effectively to stakeholders both internally and externally, driving data-driven decision making
• Collaborate with cross-functional teams, including software engineers, domain experts, and business analysts, to understand requirements and deliver integrated solutions, end-to-end data solutions
• Create and maintain comprehensive documentation for data architectures, code, algorithms, and models. Ensure that the knowledge is shared and accessible within the team
• Act on client feedback constructively to improve services and outcome, serving as a key technical contact for data-related discussions
• Continuously seek ways to enhance the overall customer experience, proactively identifying and addressing complex data challenges
• Stay updated on the latest developments in cloud data services,machine learning, data science, and analytics
• Drive innovation by evaluating, proposing, and implementing cutting-edge techniques and technologies to address client challenges

Skills

• Expert-level understanding and experience with SQL and relational database concepts
• Deep understanding of database technologies, data warehouses, and ETL tools (e.g., MySQL, PostgreSQL, Beam, Airflow, and Kafka). Proven track record of designing and implementing scalable data pipelines
• Advanced experience with data analysis tools (eg., Jupyter, Colab, Pandas)
• Extensive experience with data visualization tools (eg., Tableau, Looker, PowerBI, Qlik, and SuperSet)
• Demonstrated experience developing comprehensive data strategies and facilitating data migrations into production systems
• Expertise with cloud platforms (e.g., AWS, Azure, GCP)
• Proficiency in programming languages such as Python, Java, or C++
• Strong software engineering skills with an emphasis on writing clean, modular, and maintainable code
• Experience with version control systems (e.g., Git) and collaborative development workflows
• Exceptional problem-solving and critical-thinking skills
• Effective communication skills and ability to work in a collaborative team environment
• Bachelor's or advanced degree in Computer Science, Data Science, Machine Learning, or a related field
• Experience with other database technologies (eg., NoSQL, Graph)
• Any of the below cloud certifications: Google Cloud Professional Cloud Architect, Google Cloud Professional Database Engineer certification, Google Cloud Professional Data Engineer
• Experience with additional data processing tools and technologies (e.g., Spark, Hadoop)
• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes)

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