Senior Data Engineer

Data Engineer

Location:

Remote position (Office is in Manchester/candidates will need to be UK based) Salary:
Competitive plus excellent benefits Start: ASAP Ideal skills:
Ideally 3 years experience as a Data Engineer, AWS is essential (Used commercially), a keen interest in AI & ML, DBT, Python, Redshift, Airflow, AI Tooling.

Who we are:

Founded in 2003, Mobysoft provides data-based insight solutions to a wide range of social housing clients, supplying technology to help landlords to improve their income-collection processes for the good of all involved. Mobysoft delivers two market-leading products, which help keep tenants housed in a home they can enjoy and simultaneously improves rent collection for the long term good of the organisation.

Our vision is working towards a world in which intelligent technology significantly improves the quality of life for people who live in social housing and our mission is delivering accurate actionable data insights that help social housing providers to deliver a more consistent and equitable service

What are we looking for?

We are an ambitious, customer-centric Data & Insights team, dedicated to developing a new generation of data products that unlock significant value for the social housing sector. We operate with a focused product lens, driven by curiosity and a commitment to technical excellence. Data Engineering is foundational to this mission, ensuring synchronized, curated, trusted, dynamic data is available at speed and scale for our clients, data analysts, data scientists, and stakeholders.

As such we are looking for a Data Engineer (DE) professional to join our dynamic team, working with our most excellent existing Senior Data Engineer, to help us deliver some key Data projects.

Key Responsibilities

Ingesting and understanding new data sources, evolving our data approach (e.g., to a fully-fledged data fabric), implementing and streamline MLOps processes and exploring how we can sensibly and safely utilise artificial intelligence (AI) to turbo charge our work (e.g., smart data quality monitoring, meta data curation and service optimisation).

In short there will be plenty to keep you interested, your technical and power skills developing and a real chance to drive innovation and change.

As part of this you may also be asked to liaise with our clients from time to time(directly or through events, conferences, webinars etc.), to help support their data driven journeys.

Why should you consider this role?

Alongside the work opportunities as described your development will be supported, you will be sensibly renumerated, we will provide a compelling benefits package, and we are a great bunch of folks to work with - though we would say that!

Qualifications and skills Required

• Ideally a degree in Information Systems, Computer Science, Information Technology, Software Engineering or similarly related and quantitative discipline.

• AWS - You have worked with this commercially & an essential skill for this role.

• Circa 3 years of commercial experience working primarily in an AWS Cloud environment using approaches/tooling like ours (see technical skills), delivering scalable, performant, reliable solutions.

• Strong data reliability/observability, data governance and information security credentials.

What technical skills are required? ETL/ELT & Data Transformation:

• Amazon Redshift (query tuning, distribution/sort keys, workload management)

• Data modelling (normalisation, dimensional)

• dbt (modeling, testing, documentation, deployment)

• Building scalable ETL/ELT pipelines with Python

Workflow Orchestration:

• Apache Airflow (DAG design, scheduling, monitoring, scaling)

• Best practices for dependency management, retries, and alerting

Cloud & Serverless

• AWS Lambda (Python-based serverless pipelines, event-driven processing)

• IAM roles, policies, and security best practices

Programming & Scripting

• Python (data processing, automation, testing)

• SQL (advanced query writing and optimization)

Data Engineering Best Practices

• CI/CD for data pipelines (Git, Git Hub Actions, etc.)

• Data quality checks, monitoring, and observability

• Infrastructure as Code (Terraform etc.)

Other Tools & Ecosystem

• Experience with logging/monitoring

• Exposure to data governance, cataloguing, and lineage tools

• Ability to work with a range of structured, semi-structured and unstructured file formats including Parquet, json, csv, xml, pdf, jpg.

• Tools and methods to develop comprehensive data reliability and active metadata solutions.

• Ability to work with and develop APIs (including data transformations).

• Ability to deliver data deidentification and anonymisation solutions.

• Understanding of Cloud security frameworks (specifically on the AWS Cloud) including appropriate data encryption

Desirable

• Utilising AI within data engineering to drive performance

• Facilitating search tools such as Solr

• MLOps experience including familiarity with tools such as DVC & mlflow

• Full data engineering cycle knowledge (tools and skills) for stream data

The Person

You are someone who:

• Takes…