The Senior Data Engineer role will work on designing, building, and implementing data solutions to support strategic analytics projects & initiatives that drive strategic growth for ADM. This involves liaising with functional teams that generate or acquire data, application owners to understand raw or source data structures, and end users to accurately design and build strategically significant Data centric projects.
The ideal candidate will have an interdisciplinary mindset able to connect data engineering with AI/ML, software development and business needs. They will be equally comfortable working independently on complex problems or embedded in a cross-functional team.
- Develop cloud-native applications that integrate data services, APIs and analytics.
- Design, develop, test and document data integrations and assist with deployment, validation and hyper-care processes.
- Collaborate with data scientists, AI engineers, product managers, and business stakeholders to translate requirements into production-ready solutions.
- Develop prototypes and proof of concepts as part of the solutioning process.
- Lead engineering efforts from architecture through delivery.
- Contribute to high level solution/project design.
- Document solutions through high/low level design documentation.
- Maintain and support existing ETL/ELT integrations leveraging technical documentation.
- Develop and maintain existing codebases as needed.
- Understand and navigate a wide array of source data systems (enterprise data warehouses, relational databases, IT systems, in house and COTS applications, documents, APIs, unstructured data, big data, NoSQL databases, etc.).
- Synthesise & communicate ideas and recommendations to colleagues and management.
- Recommend solutions to address gaps in current data processes.
- Assist with project development estimation (epics, stories, features, bugs).
- Mentor junior engineers and contribute to engineering best practices.
Your Profile:
- Bachelor s Degree in Business Analytics, Statistics, Computer Science or related field.
- 7+ years of experience performing data mining, data analytics and predictive modeling initiatives.
- Significant SQL Scripting / TSQL development experience.
- Significant Experience in a number of programming languages (e.g. Python, Java, Scala, C#, JS, R).
- Proven data processing (ETL/ELT), data mining, data analytics and predictive modeling abilities.
- OLAP & OLTP database development experience with relational databases like MSSQL Server/Oracle & Postgres.
- Understanding of data warehousing and data mart concepts.
- Significant Azure Cloud experience (Administration, Data engineering & Networking).
- Experience with pipelining tools (ADF/Azure Synapse/Databricks Pipelines preferred).
- Experience with MPP systems, Azure Synapse/Databricks preferred.
- Familiarity with supervised and unsupervised machine learning techniques.
- Experience of working within an Agile development framework.
- Unit & Integration testing experience (concepts such as TDD) and experience of frameworks (such as SSDT, Pytest).
- Strong DevOps implementation/execution experience (source control, CI/CD, release environment management).
- Demonstrated ability to work independently, lead initiatives, and thrive in collaborative team environments.
- Understanding of data modeling, architecture, and performance optimization for both structured and unstructured data.
Preferred additional experience:
- Specific SAP S4 Hana integration experience (schema, modules).
- Salesforce Integration experience (adf salesforce bulk api).
- Understanding of GenAI fundamentals (Large language models (LLMs), Retrieval Augmented Generation, embeddings, direct and indirect search methods).
- AI engineering experience (LLM integrations, fine tuning, prompt engineering and productionising GenAI solutions).+
