Responsibilities:
1. Deploy machine learning models to production and implement measures to monitor their performance.
2. Implement ETL pipelines and orchestrate data flows using batch and streaming technologies based on software engineering best practices.
3. Define, document, and iterate data mappings based on concepts and principles of data modeling.
4. Re-engineer data pipelines to be scalable, robust, automatable, and repeatable.
5. Navigate, explore, and query large scale datasets.
6. Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
7. Identify and resolve data issues including data quality, data mapping, database, and application issues.
8. Implement data flows to connect operational systems, data for analytics, and business intelligence (BI) systems.
9. Deliver high quality implementation and documentation for critical functionality.
10. Deliver code, unit tests, feature tests, stubs, and integration tests.
11. Operate in an agile environment as part of a scrum team and participate in sprint rituals.
12. Work with team members to understand designs, functional requirements, and triage issues.
13. Stay engaged with the latest technological developments, especially in the fields of generative AI.
Qualifications:
1. Strong proficiency in Python.
2. Extensive experience with cloud platforms (AWS, GCP, or Azure).
3. Experience with:
1. Data warehousing and lake architectures.
2. ETL/ELT pipeline development.
3. SQL and NoSQL databases.
4. Distributed computing frameworks (Spark, Kinesis, etc.).
5. Software development best practices including CI/CD, TDD, and version control.
6. Containerization tools like Docker or Kubernetes.
7. Experience with Infrastructure as Code tools (e.g., Terraform or CloudFormation).
4. Strong understanding of data modeling and system architecture.
5. Demonstrable experience on at least one AI/ML project.
6. Knowledge of common machine learning frameworks and models.
7. A good understanding of approaches to monitoring ML models in production.
Communication and Collaboration:
1. Communicate effectively verbally and in writing, demonstrated through:
1. Effectively explaining complex technical solutions to a non-technical audience.
2. Writing meaningfully to deliver clear information and guidance.
3. Giving impactful presentations, articulating key points clearly.
2. Demonstrate critical thinking by:
1. Analyzing and evaluating information.
2. Using information gathered to present solutions and reach decisions.
3. Displaying familiarity and comfort with a breadth of technologies (appropriate to the level of the role) and an appreciation of how they can be combined and applied to solve customer problems.
3. Work in partnership with others to:
1. Effectively manage both internal and external stakeholders to ensure synergy.
2. Collaborate meaningfully with all parties to ensure outcomes are reached effectively.
Additional Information:
Experience in a consultancy is beneficial, but demonstrable experience in working with clients/external partners in other settings will always be considered.
Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance, which requires 5 years continuous UK address history at the point of application.
About Accenture:
Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology, and operations, with digital capabilities across all of these services. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual, and Integrity.
Salary: Competitive salary and package (Depending on level of experience)
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