Experienced Associate Data Engineer

Foundational Knowledge of Technology:Demonstrates a foundational knowledge of technology concepts and applications and how they can be applied to solve real-world problems.

Additionally, the ability to stay updated with the latest technological trends and advancements are essential.

Problem Solving and Analytical Skills: Leverage strong analytical and problem-solving skills to address complex business challenges, validate and interpret data, and provide insightful recommendations that drive strategic and executional decisions.

Client Relationship Management: Build and maintain strong, trusted relationships with clients, acting as a trusted advisor.

Demonstrate a deep understanding of client needs and ensure that engagements are aligned with client objectives and strategic outcomes.

Team Collaboration: Collaborate effectively within diverse teams and with external stakeholders.

Utilize excellent interpersonal skills to manage resources and build positive working relationships across various levels, ensuring cohesive team dynamics.

Communication Skills: Exhibit clear and persuasive communication skills, both verbally and in writing.

Articulate ideas, solutions, and insights effectively to ensure recommendations and findings are well-understood by clients and team members.

Professionalism and Integrity: Uphold high standards of professional conduct and demonstrate integrity in all interactions.

Commit to ethical practices and transparency, building trust and credibility with clients, team members, and stakeholders.

Continuous Learning and Adaptability: Embrace a growth mindset and demonstrate a commitment to continuous learning.

Stay current with industry trends and leading practices, and show flexibility to handle ambiguity and adapt to the changing needs of the team and clients.

Bachelor's or Master's degree in disciplines with an analytical and quantitative component.

Preferred fields of study include, but are not limited to, Accounting, Actuarial Science, Business Analytics, Computer Science, Engineering, Information Systems, Mathematics, Statistics, or Software Engineering.

Possess a minimum of 2 – 3 years of experience in the data industry.

Passion for technology, with experience in one or more of the following areas:

Data: Demonstrates a foundational understanding of data structures, database systems, and data processing techniques.

Experience and qualifications in the following areas are an added advantage:

Knowledge or experience in data management frameworks, including operating model, data governance, data management, data security, data quality and data architecture 

Understanding of big data and cloud technologies:

Big data platforms (e.g. Cloudera, HortonWorks)

Cloud technologies and ETL services (e.g. AWS, AWS Glue, Azure, Azure Data Factory, Google Cloud, Google Cloud Dataflow)

Cloud data warehouses (e.g. Snowflake, Amazon Redshift, Azure Synapse Analytics)

Knowledge in data integration and management:

ETL tools (e.g. Informatica PowerCenter, Oracle Data Integrator, SAP Data Services, SSIS, Alteryx, KNIME)

API management (e.g. Apigee, MuleSoft, AWS API Gateway)

Understanding of data quality

Data quality tools (e.g. Trillium Software, SAS Data Quality, SAP Data Quality Management)

Analytics: Showcases a solid grasp of analytical methods, Large Language Models, machine learning algorithms, and the use of automation tools to derive insights and streamline processes.

Experience and qualifications in the following areas are an added advantage:

Prior experience in the design and execution of projects related to Data Analytics, Data science and digital transformation and up-to-date on methods and technologies related to Data Science, Artificial Intelligence/Machine Learning and Automation

Experience in working with Large Language Models

Knowledge in Business Intelligence tools, relational or graph database management tools and relevant statistic tools/programming languages (e.g. SQL, NoSQL, R, Python, SAS, VBA, C++, Java) 

Data Storytelling and visualization skills (e.g. PowerBI, Tableau or QlikView)

Other tools/cloud platform knowledge and experience valued (e.g. Alteryx, GCP, Azure, AWS)

Technologies: Exhibits familiarity with cutting-edge emerging technologies and their practical applications in various domains.

Experience and qualifications in the following areas are an added advantage:

Emerging technologies (e.g. GenAI, Blockchain and other key domains)

Experience in solution architecture (e.g. Cloud, application development and integration)

Functional expertise in Enterprise Apps (e.g. CRM, Billing, SCM, or ERP systems)

Strong analytical and problem-solving capabilities, with the ability to work comfortably with large, complex data sets.

Strong project management capabilities, including the ability to prioritize and manage multiple tasks.

Expertise in business consultancy and advisory, including experience in process mapping, analysis, and risk management.

Ability to understand and translate business requirements into technical solutions, with a strong business acumen.

Excellent communication and presentation skills, both oral and written.

Ability to collaborate effectively with diverse stakeholders and maintain a client service mindset to build and maintain relationships.