Data Engineer

Halian | Managed Services, Recruitment Agency & Contract Staffing; Norwich; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Pension

Hybrid working

Training & Development

Career progression

Company benefits

Job summary

Halian is hiring a Data Engineer to strengthen our data infrastructure. You will build and optimize data pipelines, ingest data from multiple sources, and ensure data quality across analytics environments.

The role emphasizes hands-on work with SQL, Python, and cloud data platforms, with a focus on reliable, scalable data processing and governance to support reporting and AI initiatives.

Qualifications

• Commercial experience in Data Engineering, Analytics Engineering, BI Engineering, or a closely related role.
• Strong SQL skills and experience working with relational data.
• Good Python skills for data processing and automation.
• Commercial experience building or maintaining data pipelines.
• Experience integrating data from multiple sources.
• Practical experience identifying and resolving data quality and consistency issues.
• Understanding of data modelling and analytical data structures.
• Experience with ETL or ELT processes.
• Experience working with databases, data warehouses, or cloud data platforms.
• Strong problem-solving skills and a methodical approach to investigating data issues.

Responsibilities

• Building, maintaining, and improving reliable data pipelines across multiple business systems.
• Extracting, transforming, and loading data into centralised analytical environments.
• Integrating data from multiple internal systems and external sources.
• Investigating and resolving data quality, consistency, and integrity issues.
• Identifying discrepancies between systems and establishing reliable sources of truth.
• Developing reusable data transformation and processing workflows
• Writing efficient SQL queries for data extraction, transformation, and analysis.
• Using Python to automate data processing and engineering tasks.
• Supporting the development and maintenance of data warehouses and analytical data structures.
• Monitoring data pipelines and investigating failures or unexpected results.
• Working with stakeholders to understand data requirements and translate them into technical solutions.
• Documenting data sources, transformations, pipelines, and processes.
• Creating trusted datasets to support reporting, analytics, Data Science, and future AI initiatives.
• Contributing to improvements in data governance, quality, and accessibility across the organisation.

Skills

Data engineering

SQL

Python

Data pipelines

Data integration

Data quality

Data modeling

ETL/ELT

Data warehousing/cloud

Problem solving

Tools

Azure

Azure Data Factory

Databricks

Snowflake

Microsoft Fabric

dbt

APIs

Power BI

Tableau

CI/CD

Git

Data lakes

Data warehouses

Job description

BENEFITS – Pension, Hybrid Working, Training & Development, Career Progression, Company Benefits etc.

As part of our continued investment in data and technology, we are strengthening our data infrastructure to make better use of the significant volumes of information generated across the business.

We are looking to hire a Data Engineer to play a key role in improving how data is collected, integrated, structured, and made available across the organisation. This is a hands‑on role suited to someone who enjoys working with real‑world data, solving data quality challenges, and building reliable pipelines across multiple business systems and data sources.

The Data Engineer MUST have:

• Commercial experience in Data Engineering, Analytics Engineering, BI Engineering, or a closely related role
• Strong SQL skills and experience working with relational data
• Good Python skills for data processing and automation
• Commercial experience building or maintaining data pipelines
• Experience integrating data from multiple sources
• Practical experience identifying and resolving data quality and consistency issues
• Understanding of data modelling and analytical data structures
• Experience with ETL or ELT processes
• Experience working with databases, data warehouses, or cloud data platforms
• Strong problem-solving skills and a methodical approach to investigating data issues

The Data Engineer will ideally have the following attributes:

• Experience with Microsoft Azure and Azure data services
• Knowledge of Azure Data Factory or similar orchestration tools
• Experience with Databricks, Snowflake, or Microsoft Fabric
• Experience with Azure SQL
• Knowledge of dbt or similar data transformation frameworks
• Experience working with data lakes or cloud data warehouses
• Experience integrating data through APIs
• Knowledge of Power BI, Tableau, or similar visualisation tools
• Understanding of data quality and governance frameworks
• Experience with CI/CD or automated testing for data pipelines
• Experience supporting machine learning or AI projects
• Basic understanding of statistics, machine learning, or Data Science
• Experience using Git or another version control system
• Excellent communication skills and the ability to work with technical and non‑technical stakeholders

The Data Engineer role will involve:

• Building, maintaining, and improving reliable data pipelines across multiple business systems
• Extracting, transforming, and loading data into centralised analytical environments
• Integrating data from multiple internal systems and external sources
• Investigating and resolving data quality, consistency, and integrity issues
• Identifying discrepancies between systems and establishing reliable sources of truth
• Developing reusable data transformation and processing workflows
• Writing efficient SQL queries for data extraction, transformation, and analysis
• Using Python to automate data processing and engineering tasks
• Supporting the development and maintenance of data warehouses and analytical data structures
• Monitoring data pipelines and investigating failures or unexpected results
• Working with stakeholders to understand data requirements and translate them into technical solutions
• Documenting data sources, transformations, pipelines, and processes
• Creating trusted datasets to support reporting, analytics, Data Science, and future AI initiatives
• Contributing to improvements in data governance, quality, and accessibility across the organisation