Data Engineer
- 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
- You have 3+ 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
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