Data Engineer

Role Overview

AIVION is expanding its Data & AI consulting capability and is looking for a Data Engineer with 4+ years of experience to support client delivery across data engineering, analytics, reporting, and modern data platform projects.

This role will be particularly useful as AIVION opens new client accounts, where clients need support with data pipelines, data warehousing, reporting datasets, analytics platforms, and AI-ready data foundations.

The ideal candidate should have strong SQL skills, practical data engineering experience, and the ability to work with cloud data platforms, ETL/ELT tools, reporting datasets, and business-facing data requirements.

Key Responsibilities

Data Engineering & Pipeline Development

• Build, maintain, and optimise data pipelines from multiple source systems into centralised data platforms.
• Develop ingestion, transformation, validation, and reconciliation processes.
• Work with structured and semi-structured data from databases, files, APIs, SharePoint, Excel, and other business systems.
• Support the creation of staging, canonical, history, and reporting layers.
• Implement reusable data engineering patterns and maintain clean, well-documented code.

SQL, Data Modelling & Transformation

• Write efficient SQL queries, stored procedures, views, and transformation logic.
• Support dimensional modelling and reporting data model design.
• Build data marts and curated datasets for business reporting, dashboards, and analytics.
• Apply data quality checks, exception handling, and validation rules.
• Support transformation frameworks such as DBT or similar tools.

Cloud Data Platform Support

• Work with cloud data platforms such as Snowflake, Azure SQL, PostgreSQL, or similar.
• Support data loading, scheduling, orchestration, and monitoring.
• Assist with platform configuration, access control, performance tuning, and cost-aware design.
• Work with ETL/ELT tools such as Matillion, DBT, Azure Data Factory, Airflow, or similar technologies.

Business Reporting & Analytics Enablement

• Prepare reliable datasets for tools such as Power BI, Sigma, Excel, or other BI platforms.
• Work with analysts and business users to understand reporting and data requirements.
• Support dashboard development by preparing clean, consistent, and well-structured datasets.
• Help users understand data lineage, definitions, and business rules.

Client Delivery Support

• Work on client projects across financial services, trading, brokerage, risk, finance, operations, and compliance domains.
• Participate in workshops to understand source systems, data requirements, reporting needs, and data quality challenges.
• Document data flows, transformation logic, data mappings, and technical decisions.
• Support client demonstrations, testing, issue resolution, and production handover.

Required Skills & Experience

• 4+ years of experience in data engineering, BI engineering, or analytics engineering.
• Strong SQL skills, including joins, aggregations, window functions, CTEs, and query optimisation.
• Experience building ETL/ELT pipelines and data transformation workflows.
• Experience with at least one modern data platform such as Snowflake, PostgreSQL, SQL Server, Azure SQL, BigQuery, or Redshift.
• Experience working with data from files, databases, APIs, and business applications.
• Understanding of data modelling concepts, including staging, history, canonical, and reporting layers.
• Good knowledge of data quality, reconciliation, validation, and exception handling.
• Ability to document data mappings, transformation rules, and technical workflows.
• Good communication skills and ability to work with both technical and business stakeholders.

Desirable Skills

• Experience with Snowflake, Matillion, DBT, Power BI, Sigma, or Azure Data Factory.
• Python experience for data processing, automation, or scripting.
• Experience in financial services, brokerage, trading, risk, finance, or regulatory reporting.
• Understanding of data governance, data catalogues, business glossary, and metadata management.
• Experience with Git, CI/CD, scheduling tools, and production support processes.
• Exposure to AI/ML data preparation, feature engineering, or analytics use cases.

Candidate Profile

The ideal candidate will be:

• Strong in SQL and practical data engineering.
• Comfortable working with messy, real-world business data.
• Able to understand business requirements and convert them into reliable datasets.
• Detail-oriented, especially around data quality, reconciliation, and accuracy.
• Willing to work in a consulting environment with different clients and changing priorities.
• Proactive, curious, and comfortable learning new tools and domains.

Why This Role Matters

AIVION is building a strong Data & AI consulting practice for SME financial services and other growing businesses. Many clients need help creating modern data platforms, improving reporting, automating manual data processes, and preparing their data foundations for AI adoption.

This role will help AIVION deliver high-quality data engineering work for new client accounts and strengthen our ability to scale consulting delivery beyond the founding team.