Senior Data Engineer

EC Markets UK; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

EC Markets is building a Snowflake-based Data Lakehouse to power trading, operational and marketing analytics. We are seeking a Senior Data Engineer to drive evolution of the data platform, enabling scalable ingestion, transformation and governance across the business.

This role focuses on architecting the data layer, implementing robust ETL/ELT pipelines, and delivering governance-ready data for MI dashboards and regulatory reporting.

Qualifications

• 5–8 years hands-on data engineering/analysis experience.
• Degree in Computer Science, Data Engineering, or related field.
• Experience designing DWH/Delta Lakehouse using Snowflake.
• Proficiency with SQL, data modelling (star/snowflake schemas) and Power BI.

Responsibilities

• Own Snowflake-centric Data Lakehouse architecture and data models.
• Develop ETL/ELT pipelines ingesting data from multiple internal systems.
• Deliver semantic models, reports, dashboards and data extracts.
• Ensure data governance, privacy, and regulatory compliance.

Skills

Analytical thinking

Communication

Regulatory awareness

Financial domain knowledge

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

dbt

Power BI

AWS

Terraform

GitHub Actions

Job description

EC Markets is building a next-generation data platform to power trading, operational, and marketing intelligence. We are seeking a Senior Data Engineer to drive evolution of our Snowflake-based Data Lakehouse, establishing a modern data ecosystem that supports advanced analytics, compliance, and decision-making across the business.

This is a high-impact role for an experienced engineer with a track record of architecting and implementing scalable data platforms - ideally in financial or trading environments - who can talk and think data from ingestion to MI dashboards.

Key Responsibilities

• Assume ownership of a Snowflake-centric Data Lakehouse integrating structured, semi-structured, and unstructured data.
• Develop and support robust ETL/ELT pipelines that ingest and transform data from multiple internal systems (trading, CRM, finance, risk, etc.) and external APIs.
• Implement data models, schemas, and transformation frameworks optimised for analytical and regulatory use cases.
• Apply best practices in data versioning, orchestration, and automation using modern data engineering tools.
• Ensure scalability, data lineage, and governance across the data lifecycle.

Reports and data visualisation

• Build and own semantic models on top of Snowflake (DirectQuery and Import), using DAX, calculation groups, RLS/OLS, and incremental refresh.
• Develop operational reports, dashboards and data extracts

Data Governance & Quality

• Maintain high data integrity, privacy, and security aligned with FCA and GDPR requirements.
• Monitor and optimise query performance and storage efficiency.

Cross-Functional Collaboration

• Partner with business units (Trading, Finance, Marketing, Compliance, Operations) to capture data requirements and translate them into robust technical solutions.
• Support regulatory, management, and operational reporting requirements through structured data models.

Skills & Experience (Non-negotiable)

• Experience in financial services, trading, or fintech environments.
• Proven experience designing and delivering DWH / Delta Lakehouse using Snowflake.
• Expert level SQL and data modelling expertise (star/snowflake schemas, dimension/al modelling).
• 2+ years writing dbt models in production. Comfortable with sources, snapshots, tests, macros, exposures, and the medallion (bronze/silver/gold) pattern.
• 3+ years building production Power BI on enterprise warehouses. Expert DAX (time intelligence, variables, virtual relationships, calculation groups), Power Query / M, Tabular Editor, DAX Studio.
• Strong SQL on Snowflake. Understand warehouse sizing, clustering, query profiles, and the cost levers that matter.
• Familiarity with orchestration and transformation frameworks.
• Hands‑on experience with data analysis, visualisation, and operational reporting tools.
• Excellent communication skills and ability to translate business requirements into scalable data architecture.

Skills & Experience (nice to have)

• Ability to create scripts in Python or another scripting language.
• Experience with AWS (ECS, S3, IAM), Terraform, Git/GitHub Actions.
• Power BI embedded, Fabric, or a credible opinion on when not to use them.
• Exposure to Microsoft Fabric Direct Lake, Snowflake Cortex / Claude.ai connector, or other AI-on-warehouse patterns.

Qualifications

• Degree in Computer Science, Data Engineering, or related field.
• 5-8 years of hands‑on experience in data engineering and / or analysis.