
Big Data Infrastructure Specialist
4 days ago
About Fusemachines
Fusemachines, a leader in AI strategy, talent, and education services, drives innovation through democratized AI. With a presence in 4 countries and over 400 employees, Fusemachines seeks to empower businesses worldwide.
About the Role
This role involves designing, developing, and maintaining large-scale data infrastructure for integration, storage, processing, and analytics. As a Senior Data Engineer, you will contribute to Agile development environments, focusing on data quality, performance, and cost optimization.
Qualifications & Experience
- A Bachelor's degree in Computer Science or similar.
- At least 5 years of experience as a data engineer with expertise in Databricks, Azure, DevOps, or other hyperscalers.
- Experience with Azure DevOps, GitHub, and delivering large-scale projects and products for Data and Analytics, including migrations.
- The following certifications:
- Databricks Certified Associate Developer for Apache Spark
- Databricks Certified Data Engineer Associate
- Microsoft Certified: Azure Fundamentals
- Microsoft Certified: Azure Data Engineer Associate
- Microsoft Exam: Designing and Implementing Microsoft DevOps Solutions (nice to have)
Required Skills/Competencies
- Strong programming skills in Python, Scala, and SQL, with proficiency in writing efficient and optimized code.
- Experience with big data principles, techniques, and best practices.
- Knowledge of scalable and distributed Data Processing Technologies such as Spark/PySpark, DBT, and Kafka.
- Experience in designing and implementing efficient ELT/ETL processes in Azure and Databricks.
- Skilled in Data Integration, data cleansing, transformation, and validation.
- Proficiency with Relational Databases and NonSQL Databases.
- Understanding of Data Modeling and Database Design Principles.
- Experience in designing and implementing Data Warehousing, data lake, and data lake house solutions.
- Understanding of DevOps principles, including CI/CD, IaC, configuration management, automated testing, and cost management and optimization.
- Knowledge in cloud computing specifically in Microsoft Azure services related to data and analytics.
- Experience in Orchestration using technologies like Databricks workflows and Apache Airflow.
- Knowledge of data structures and algorithms and good software engineering practices.
- Proven experience migrating from Azure Synapse to Azure Data Lake, or other technologies.
- Strong analytical skills to identify and address technical issues, performance bottlenecks, and system failures.
- Proficiency in debugging and troubleshooting issues in complex data and analytics environments and pipelines.
- Understanding of Data Quality and Governance.
- Experience with BI solutions including PowerBI is a plus.
- Strong written and verbal communication skills.
- Ability to document processes, procedures, and deployment configurations.
- Understanding of security practices, including network security groups, Azure Active Directory, encryption, and compliance standards.
- Ability to implement security controls and best practices within data and analytics solutions.
- Self-motivated with the ability to work well in a team, and experienced in mentoring and coaching different members of the team.
- A willingness to stay updated with the latest services, Data Engineering trends, and best practices in the field.
- Comfortable with picking up new technologies independently and working in a rapidly changing environment with ambiguous requirements.
- Care about architecture, observability, testing, and building reliable infrastructure and data pipelines.
Responsibilities
- Architect, design, develop, test, and maintain high-performance, large-scale, complex data architectures.
- Contribute to detailed design, architectural discussions, and customer requirements sessions.
- Actively participate in the design, development, and testing of big data products.
- Construct and fine-tune Apache Spark jobs and clusters within the Databricks platform.
- Migrate out of Azure Synapse to Azure Data Lake or other technologies.
- Assess best practices and design schemas that match business needs for delivering a modern analytics solution.
- Design and implement data models and schemas that support efficient data processing and analytics.
- Design and develop clear, maintainable code with automated testing.
- Collaborate with cross-functional teams to understand data requirements and develop data solutions.
- Evaluate and implement new technologies and tools to improve data integration, data processing, storage, and analysis.
- Evaluate, design, implement, and maintain data governance solutions.
- Continuously monitor and fine-tune workloads and clusters to achieve optimal performance.
- Provide guidance and mentorship to junior team members.
- Maintain clear and comprehensive documentation of the solutions.
- Promote and enforce best practices in data engineering, data governance, and data quality.
- Ensure data quality and accuracy.
- Design, implement, and maintain data security and privacy measures.
- Be an active member of an Agile team.
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