Data Engineer / Senior Data Engineer

Job Description

hackajob is collaborating with Raytheon to connect them with exceptional professionals for this role.

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As a Data Engineer, you will be critical to the successful delivery of the programme, collaborating within matrix organisation, with multi-disciplinary teams within Engineering.

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We are looking for individuals who want to serve. You’ll have a mission focus, and the enthusiasm and drive to deliver. You must be eligible and willing to obtain SC clearance and will be based at Warminster working in a hybrid style.

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You’ll work in a matrix organisation and report operationally through OMNIA Training and functionally to the Data Lead. Ultimately, you’ll work for the British Army, championing innovation, and helping shape the future of military collective training.

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Key Responsibilities:

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• \nCollaborate with engineering, simulation, customer, third party and training teams to ensure seamless data management and integration across military training environments.\n

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• \nEnsuring the security and compliance of data environments through the implementation of appropriate security controls and governance frameworks.\n

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• \nAuthor, review and contribute to technical documentation.\n

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• \nCoordinate with cross-functional engineering teams—including QA, development, operations, and business SMEs.\n

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• \nAssist in the design and implementation of scalable, high-performance data platforms and pipelines.\n

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• \nDefine and enforce data engineering standards, best practices, and governance frameworks including data lifecycle design, implementation and management.\n

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• \nImplement the design and optimisation of data storage, processing, and retrieval strategies.\n

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• \nCollaborate with cross-functional teams (data scientists, analysts, software engineers) to align data solutions with business needs.\n

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• \nDrive adoption of modern data technologies (e.g., cloud-native platforms, streaming, orchestration tools).\n

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• \nContribute to data quality, security, compliance, and lineage practices across the organisation.\n

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• \nProvide technical input and guidance to data engineering team members.\n

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• \nEvaluate, select, and integrate new tools, frameworks, and platforms for the data ecosystem.\n

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• \nAct as a subject matter expert in data strategy, influencing design decisions.\n

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• \nAny other duties required to meet the needs of the programme.\n

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Who we are looking for:

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The OMNIA Data Engineer will provide hands-on technical oversight and management across the Army Collective Training Service (ACTS) data solutions. These will be prominently MODCloud hosted utilising Cloud Services from AWS, Azure, OCP where appropriate. Reporting to the Data Architect, you will play a key role in ensuring the effective design, assurance, transformation, and delivery of data across ACTS services and capabilities. This includes supporting the integration and operational use of data from legacy systems through API-driven solutions.

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This role requires a systems-thinking mindset, strong stakeholder engagement skills, and the ability to work across engineering teams in a complex and evolving environment. Given the programme’s focus on modelling and simulation, familiarity with relevant standards and technologies is highly desirable.

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Essential Skills and Experience:

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• \nHands-on experience with cloud platforms (AWS, Azure, GCP, OCI) and cloud-native data services.\n

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• \nExtensive experience designing and building large-scale data pipelines and platforms.\n

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• \nStrong expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL).\n

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• \nProficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop).\n

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• \nDeep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services.\n

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• \nStrong programming skills in Python, Java, or Scala for data engineering.\n

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• \nHands-on experience with data orchestration and workflow management tools (e.g., Airflow, Dagster, Prefect).\n

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• \nProven track record with data governance, quality, lineage, and security practices.\n

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• \nExperience with real-time/streaming data technologies, data Ingestion / ETL (e.g., Apache Kafka, Apache NiFi, Kinesis, Pub/Sub).\n

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• \nStrong proficiency in relational and non-relational databases (e.g., PostgreSQL, MongoDB, Cassandra).\n

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• \nDeep knowledge of data transformation and ETL pipelines and APIs.\n

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• \nSecurity cleared or ability to obtain (SC or above).\n

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Desirable Skills and Experience:

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• \nDegree in Data Engineering or equivalent professional accreditation such as CEng.\n

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• \nExperience with graph databases and advanced query languages (e.g., Neo4j, Gremlin).\n

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• \nKnowledge of machine learning data pipelines and MLOps practices.\n

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• \nFamiliarity with data virtualisation and data mesh concepts.\n

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• \nHands-on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift and Ceph).\n

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• \nExposure to infrastructure-as-code tools (Terraform, CloudFormation).\n

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• \nExperience with BI/visualisation tools (e.g., Tableau, Power BI, Looker, Elastic Stack).\n

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• \nKnowledge of compliance frameworks (GDPR, HIPAA, CCPA) and their impact on data systems.\n

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• \nStrong background in performance tuning for high-throughput, low-latency data systems.\n

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• \nMicrosoft Certified: Azure Data Engineer Associate, AWS Certified Data Engineer, IBM Data Engineering Professional Certificate or similar.\n

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