Data Analytics Engineer: Real-Time Insights & Modeling

Seccl; Greater London; Hybrid; GBP 55,000 - 75,000; Full time

Benefits offered by this job

MacBook provided

Home office budget

Learning budget £750

Private medical insurance

Pension 6%

Cycle to Work

Job summary

Seccl is hiring a Data Analytics Engineer to join our Data Engineering team. You’ll design production-quality datasets, using SQL and DBT, and work closely with Product, Engineers, Operations and clients to solve real business problems.

You’ll drive data movement toward real-time processing, exploring MongoDB change streams, Kafka and AWS MSK, while ensuring datasets are well documented and easy to consume.

Qualifications

• Strong SQL and data modelling skills.
• Experience with Python and DBT with testing, documentation and CI/CD.
• Familiar with relational and non-relational databases.
• Understanding of dimensional modelling for analytics.
• Experience with cloud data platforms, ideally AWS.
• Experience with event-driven/streaming architectures (Kafka, AWS MSK, MongoDB Change Streams, CDC).
• Hands-on experience with Airflow.
• Thrives in cross-functional collaboration.
• Ability to own problems end-to-end.

Responsibilities

• Design, build, and maintain robust data models using SQL and DBT.
• Collaborate with Product, Engineers, Operations and clients to translate requirements into data solutions.
• Define, maintain metrics and analytics standards across the business.
• Support real-time and incremental data processing with streaming tech.
• Make datasets well-documented and easy to consume.

Skills

SQL modelling

Python

DBT

Relational DB

NoSQL

Dimensional modelling

AWS

Kafka

MongoDB Change Streams

Airflow

Collaboration

Tools

DBT

Airflow

AWS MSK

Job description

Seccl is hiring a Data Analytics Engineer to join our Data Engineering team. You’ll design production-quality datasets, using SQL and DBT, and work closely with Product, Engineers, Operations and clients to solve real business problems.

You’ll drive data movement toward real-time processing, exploring MongoDB change streams, Kafka and AWS MSK, while ensuring datasets are well documented and easy to consume.