Senior Data Engineer
NTT Data
Senior Engineer in Production Management (Big Data - Snowflake Focused)
The Senior Engineer in Production Management, specializing in Big Data with a focus on Snowflake, will be responsible for the design, development, and overall implementation of robust and scalable data solutions in a complex, critical, and large cross-departmental and multi-disciplinary area. This role is crucial for building robust pipelines, ensuring data quality, and driving performance improvements across our Big Data initiatives..
The role requires a comprehensive understanding of various facets of Big Data technologies and how they interact to achieve strategic data objectives. The candidate will apply in-depth understanding of the business impact of data-driven insights and be accountable for the delivery of a full range of end-to-end data engineering projects.
Responsibilities:
- Demonstrates an in-depth understanding of the Software Development Lifecycle and its integration within the overall data technology landscape to deliver scalable, reliable, and performant Big Data solutions, particularly within Snowflake.
- Conduct in-depth data analysis, troubleshoot complex data issues, and ensure the accuracy, reliability, and integrity of data.
- Optimize Big Data workflows, including Snowflake query optimization, leveraging partitioning strategies and indexing techniques in distributed storage systems.
- Perform rigorous unit testing and validation of data pipelines and transformations.
- Collaborate with data scientists, analysts, and other engineers to understand data requirements and deliver robust data solutions.
Qualifications:
- Relevant experience in a critical Big Data engineering role with high business impact, and a strong ability to understand how data solutions deliver business value.
- Excellent engineering skills with expertise in Snowflake data warehousing.
- Excellent working knowledge of key computer science concepts, especially as they apply to distributed systems, data structures, and algorithms for large-scale data processing.
- Excellent understanding of data engineering concepts like Data Modeling, Data Lakes, Data Warehouses, and Data Marts.
- Strong debugging and analytical skills: ability to isolate root causes across data pipelines, Snowflake, cloud infrastructure, and data processing layers.
- Operational experience of designing, deploying, and managing data pipelines and Snowflake solutions at scale, potentially leveraging cloud platforms (AWS) and related services.
- Operational experience with orchestration tools for CI/CD and Infrastructure-as-Code tooling (Terraform, Cloud Formation, dbt, etc.) is highly desirable for data platform automation.
- Degree in computer science/mathematics/physics or related technical subject is desirable.
- Excellent critical thinking and problem-solving skills with a strong analytical mindset.
- Ability to work independently and collaboratively in a fast-paced environment.
- Strong communication skills to articulate technical concepts and solutions effectively.
Role Skills Matrix:
Skill | Rating* |
Snowflake (Or any other Big Data solution) | 5 |
Python (Data Engineering) | 4 |
Data Warehousing Concepts | 4 |
Data Modelling (Dimensional/Relational) | 4 |
Cloud Platforms (AWS) | 4 |
SQL | 5 |
High Availability Systems (Data) | 4 |
*Ratings are 1-5, with 1 being the lowest and 5 being the highest. To interpret the numbers, use the following scale:
1 = Junior contributor, understands key concepts and can operate with close supervision
2 = Proficient contributor, fully grasps the key concepts, but no production experience
3 = Independent contributor, understands technology well and has delivered production systems
4 = Senior Independent contributor, operates the technology on the cutting edge and can implement use cases with limited community support
5 = Lead industry contributor, operates the technology on the bleeding edge and can commit changes to the technology's roadmap
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