Job Description

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