Senior Data Engineer

Falconsmartit; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Falconsmartit in London is seeking a Senior Data Engineer to design and build scalable data platforms, architect data models, and implement robust data pipelines across the stack.

You will own metadata management, data quality processes, and performance monitoring, collaborating with business and technology teams to ensure the analytics platform delivers trusted insights. Hybrid work: 2 days onsite, 3 days remote.

Qualifications

• Senior Data Engineer with strong Python and data engineering experience.
• Proven ability to design and implement data platforms and pipelines.
• Experience with cloud-native data services and modern orchestration tooling.

Responsibilities

• Architect and develop scalable data platforms and data pipelines.
• Implement, maintain, and test robust data pipelines.
• Manage metadata processes and tooling.
• Monitor performance and ensure data quality.
• Collaborate with business and tech teams to align analytics with goals.

Skills

Python

Data engineering

Tools

AWS

Snowflake

Apache Iceberg

Spark

Airflow

Prefect

Dagster

DBT

AWS Glue

Lake Formation

EMR

EventBridge

Athena

Job description

Job Title: Senior Data Engineer

Job Location: London, UK/Hybrid - 2 days Onsite and 3 Days Remote

Job Type: FTC - 1 Year

Mandatory Skillsets: AWS + Snowflake + Python

Key Responsibilities:

Architect and Develop: Contribute to the platform's architectural design and build integration, modelling, data persistence, and analytical systems.

Data Pipelines: Implement, maintain, and test robust data pipelines.

Metadata Management: Develop and manage metadata processes and tools.

Performance Monitoring: Ensure the stability and performance of data pipelines.

Data Quality: Implement tools for data curation, metadata management, and quality assurance.

Collaboration: Engage with business and technology teams to align the platform with organizational goals.

Preferred Technical Skills:

Programming: 12+ years of experience in Python.

Cloud Expertise: Strong understanding of AWS services (e.g., Lambda, Step Functions, ECS).

Data Platforms: Hands-on experience with Snowflake and data stack technologies like Apache Iceberg and Spark.

Workflow Orchestration: Exposure to tools like Apache Airflow, Prefect, Dagster, or DBT.

Data Services: Familiarity with AWS Glue, Lake Formation, EMR, EventBridge, Athena, and similar services.

Metadata Tools: Experience with tools like Amundsen, Atlas, DataHub, OpenDataDiscovery, or Marquez.

RDBMS: Knowledge of PostgreSQL is a plus.

Industry Experience: Proven experience building enterprise-wide data and analytics systems, preferably in financial services or asset management.