- Provide thought leadership and drive architecture of Enterprise Analytics / BI and Data Science solutions to deliver scalable implementations using the latest cloud technologies in AWS/Azure and 3rd party BI platforms
- Translate business goals and use cases into technical solutions to deliver actionable insights for various business processes, especially in the area of sales, finance, e-commerce, manufacturing/logistics, banking or CRM. Become the technical SPoC for all stakeholders.
- Set architectural vision and direction across a matrix of teams. Propose a conceptual/logical design for various data components and large volumes of data integrations.
- Apply effective governance methods for long-term scalability, high availability, fault tolerance, and solution elasticity in alignment with enterprise architecture, security and infrastructure guidelines and standards.
- Provide supervision and guidance to the implementation team (data engineers, data scientists, BI consultants, ..) to ensure the project is implemented as per business requirements
- Support pre-sales by proposing a technical solution and effort estimates
- Maintain an internal framework to ensure consistent & optimal delivery across projects.
- Ensure full DevOps / DataOps automation of continuous development/test/deployment processes
Requirements
- Bachelor’s or Master’s Degree in a technology-related field (e.g. Engineering, Computer Science, IT, etc.)
- 3+ years experience in design and build of data solutions, a combination of relevant areas:
- Large-scale Data Lake / Datawarehouse (DWH) solutions
- Big data pipelines / ETL / APIs (data ingestion, processing, transformation and activation) development, preferably in cloud-based tools/infrastructure
- Business Intelligence projects, using BI tools like PowerBI, Tableau, Qlick Sense, Keboola, Tibco Spotfire …
- Data Science (Machine Learning) oriented solutions
- Understanding data concepts and patterns (Data Lake, Master Data Management, data quality, lambda architectures, streaming processing)
- Having a good business acumen, especially in sales, finance, e-commerce, manufacturing/logistics, banking or CRM areas
- Proficient in architecture methodologies and tools like diagraming (draw.io, Sparks EA, Confluence) and standards (Archimate, TOGAF)
- Experience with full software development lifecycle (CI/CD), including development skills using programming languages like Python/Java/Scala/C++ and relational/NoSQL databases
- Strong analytical and complex problem-solving skills
- Strong technical leadership, mentorship and collaboration
- Strong project management and organizational skills
Preferred Skills
- Proven experience with Data Lake / Datalakehouse implementations in AWS or Azure, using MS Azure (DataBricks, Data Factory, Data Lake, Cosmos DB, Event Hub, PowerBI, ..) or AWS (Glue, EC2, EMR, RDS, Redshift, Sagemaker, …) cloud services
- Understanding of Data Science (ML) concepts from both business and technical perspective
- Experience with ERP solutions like SAP, NetSuite
- Experience with Marketing, E-commerce and CRM solutions like Salesforce (Marketing Cloud, CDP, Commerce, CRM), Adobe (AEM, Analytics) or Google (GA, BigQuery)
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