Daintta are a rapidly growing, values-driven team of specialists who work with government clients across Cyber, Telecommunications and Data. We are seeking a talented and motivated Data Engineer to join our team and contribute to our mission of protecting the UK through data-driven insights and solutions. As a Data Engineer, you will work closely with our public sector clients and project teams to develop and implement data engineering pipelines to support data science and business/mission intelligence use cases.

SKILLS/KNOWLEDGE

• You have 2+ years of degree level industry experience in data engineering, preferably in a consultancy or industry setting
• You have worked in client delivery across a range of projects, including data analysis, extraction, transformation, and loading, data intelligence, data security and proven experience in their technologies (e.g. Spark, cloud-based ETL services, Python, Kafka, SQL, Airflow)
• You have experience in assessing the relevant data quality issues based on data sources & uses cases, and can integrate the relevant data quality checks into data pipelines
• You have experience in designing schemas for data warehouses/data marts to support the relevant ingest and queries
• You have experience working on cloud-based infrastructure (e.g. AWS, Azure, GCP)
• You have demonstrable continuous personal development with relevant data certifications and accreditations
• You have strong interpersonal skills
• You are security cleared or capable and willing to undergo security clearance
• You have experience with using CI/CD tooling to analyse, build, test and deploy your pipelines and proven experience in their technologies
• You have experience in database technologies including writing complex queries against their (relational and non-relational) data stores (e.g. Postgres, Hadoop, Elasticsearch, Graph databases), and designing the database schemas to support those queries
• You have a good understanding of coding best practices and design patterns and experience with code and data versioning, dependency management, code quality and optimisation, error handling, logging, monitoring, validation and alerting

• Assessing your clients’ technical needs and understanding how their needs are different to wants and managing clients’ stakeholders relationship appropriately
• Identifying data sources, data extraction, transformation, and loading (ETL/ELT) concepts and methods
• Designing, evaluating, and implementing on-premise, cloud-based and hybrid data engineering solutions (including providing review and guidance on testing aspects related to data engineering, identification of risks and proposing and implementing their mitigations)
• Modelling, structuring and storing data along with their data flows for uses including — but not limited to — analytics, machine learning, data mining, compliance, business intelligence, sharing with applications and organisations
• Harvesting and ingesting structured and unstructured data in different formats and standards
• Integrating, consolidating and cleansing data
• Migrating and converting data
• Applying ethical principles in handling data
• Ensuring appropriate storage of data in line with relevant legislation
• Building in security, compliance, scalability, efficiency, reliability, fidelity, flexibility and portability
• Accurately delivering high quality work to agreed timelines and taking the initiative and knowing how to ‘jump straight in’
• Supporting client engagements, including pitches and presentations
• Helping to support & grow Daintta by actively inputting into the company strategy and helping to shape our future
• Representing us and our core values: Transparent, fair and daring