Data Consultant

At Ensono, our purpose is to be a relentless ally, disrupting the status quo and enabling our clients to Do Great Things. As a trusted technology adviser and managed services provider, we help clients navigate continuous change and embrace innovation. We deliver world-class hybrid cloud, infrastructure, mainframe transformation, data, IDAM, and cloud-native solutions, simplifying complex business challenges and creating new pathways to success. Headquartered in the USA and backed by private equity, Ensono has a strong and growing presence in the UK and Europe.

This is a hands-on technical role within our Data & AI competency. You will join a cross-functional team of highly skilled, like-minded professionals, helping build and deliver modern data solutions for our clients – enabling them to realise the business value of their cloud investments.

As a Data Engineering Consultant, you will design, build, and maintain data pipelines and lakehouse architectures that power analytics, AI/ML, and operational decision-making. You will work across ingestion, transformation, storage, and serving layers – delivering solutions that are scalable, reliable, and cost-efficient.

What You’ll Deliver:

• Cleaned, validated datasets and production-ready data pipeline code
• Contributions to requirements documents, data inventories, and technical specifications
• Data quality checks and monitoring dashboards for pipeline health
• Documentation supporting data governance, lineage, and cataloguing

What You’ll Be Doing:

• Building and maintaining data ingestion pipelines (batch, streaming, and micro-batch) using modern cloud-native tools and frameworks
• Developing and optimising transformations within lakehouse and medallion architecture patterns (bronze, silver, gold layers)
• Working with cloud data platforms such as Databricks, Apache Spark, and cloud-native services on AWS and/or Azure/Microsoft
• Implementing data quality checks, validation rules, and automated testing to ensure pipeline reliability
• Supporting data governance and compliance activities, including cataloguing, lineage tracking, and access control
• Collaborating with analysts, data scientists, and business stakeholders to understand requirements and deliver fit-for-purpose data products
• Contributing to technical documentation, architecture decision records, and runbooks
• Participating in code reviews, pair programming, and knowledge-sharing sessions to raise team capability

What you’ll Bring:

• Strong development skills in Python and SQL; experience writing clean, testable, well-documented code
• Hands-on experience building data pipelines and ETL/ELT workflows using tools such as Apache Spark, Databricks, or equivalent
• Understanding of lakehouse and data warehouse architecture patterns, including star schemas, medallion architecture, and data modelling best practices
• Experience working with cloud platforms (AWS, Azure, or GCP), including cloud storage, compute, and managed data services
• Familiarity with common big data file formats (e.g. Parquet, Delta, Avro) and concepts such as partitioning, compression, and columnar storage
• Good understanding of software engineering best practices: version control (Git), CI/CD, code review, SOLID principles, and DRY
• Clear communication skills – able to explain technical concepts to non-technical audiences and collaborate effectively across disciplines
• A proactive, self-starting attitude with a genuine interest in understanding the business context behind the data

Desirable Skills & Experience:

• Experience with Databricks (Delta Live Tables, Unity Catalog, Workflows) or similar lakehouse platforms
• Familiarity with Infrastructure as Code tools (e.g. Terraform, CloudFormation) and container technologies (Docker, Kubernetes)
• Exposure to data governance, cataloguing, or data quality frameworks
• Experience with TDD/BDD testing practices for data pipelines
• Knowledge of streaming technologies (e.g. Kafka, Kinesis, Spark Structured Streaming)
• Additional programming experience in Scala or Java
• Relevant cloud or data certifications (e.g. Databricks Data Engineer, AWS Data Analytics, Azure Data Engineer)

Personal & Leadership Qualities:

• Coachable and curious: You actively seek feedback, learn from experienced colleagues, and reflect on how to improve.
• Team-oriented: You contribute positively to team culture, support new joiners, and collaborate openly – building trust through reliability and approachability.
• Ownership mindset: You take responsibility for your work, communicate blockers early, and deliver to the quality and timelines expected.
• Adaptable learner: You embrace new tools, methods, and feedback. You take initiative in your own development and are energised by the pace of change in cloud and data.
• Business-aware: You seek to understand the “why” behind your work – connecting your technical delivery to client goals and business value.
• Clear communicator: You express ideas clearly in writing and conversation, listen actively, and ask good questions to build shared understanding.