Key Responsibilities:

Facilitate data, compliance, and environment governance processes for the assigned domain.
Lead analytics projects to produce insights for the business to improve decision making, delivering results using reports, business intelligence technology, or other appropriate mechanisms.
Integrate data analysis findings into governance solutions.
Ingest key data for assigned domain into the data lake, ensuring creation and maintenance of relevant metadata and data profiles.
Coach team members, business teams, and stakeholders to find necessary and relevant data when needed.
Contribute to relevant communities of practice promoting the responsible use of analytics.
Develop the capability of peers and team members to operate within the Analytics Ecosystem.
Mentor and review work of less experienced peers and team members, providing guidance on problem resolution.
Integrate data from warehouse, data lake, and other source systems to build models for use by the business.
Cleanse data to ensure accuracy and reduce redundancy.
Lead preparation of communications to leaders and stakeholders.
Design and implement data/statistical models.
Collaborate with stakeholders to drive analytics initiatives.
Automate complex workflows and processes using Power Automate and Power Apps.
Manage version control and collaboration using GITLAB.
Utilize SharePoint for extensive project management and data collaboration.
Regularly update work progress via JIRA/Meets (also to stakeholders).

External Qualifications and Competencies

Qualifications:

College, university, or equivalent degree in relevant technical discipline, or relevant equivalent experience required.
This position may require licensing for compliance with export controls or sanctions regulations.

Competencies:

Balances stakeholders: Anticipating and balancing the needs of multiple stakeholders.
Collaborates: Building partnerships and working collaboratively with others to meet shared objectives.
Communicates effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
Customer focus: Building strong customer relationships and delivering customer-centric solutions.
Manages ambiguity: Operating effectively, even when things are not certain or the way forward is not clear.
Organizational savvy: Maneuvering comfortably through complex policy, process, and people-related organizational dynamics.
Data Analytics: Discovering, interpreting, and communicating qualitative and quantitative data; determining conclusions relying on knowledge of business or functional frameworks; simultaneously applying statistics, data validity, data visualization, and problem-solving approaches to effectively extract meaningful patterns and business insights; presenting conclusions and outcomes that enable data-driven business decisions.
Data Mining: Extracting insights from data by identifying relationships and patterns through use of a suite of data exploration and data visualization techniques to understand the underlying structure of the data and enable sound conclusions upon model building.
Data Modeling: Creating, writing, and testing data models, test scripts, and build scripts using industry standards and tools, version control, and build and test automation to meet business, technical, security, governance, and compliance requirements.
Data Communication and Visualization: Constructing a tale of the business problem, root cause, solution options, and opportunities through illustrating data visually, including reports and dashboards.
Data Literacy: Expressing data in context, including data sources and constructs, analytical methods, and applied techniques; describing the use-case application and resulting value.
Data Profiling: Assessing data issues and cleansing requirements to perform data extraction, mapping, collection, and testing; establishing good, quality data.
Data Quality: Identifying, understanding, and correcting flaws in data that supports effective information governance across operational business processes and decision making.
Project Management: Establishing and maintaining the balance of scope, schedule, and resources for a temporary effort (a project). Ensuring results/impact from temporary effort are fully realized as possible.
Values differences: Recognizing the value that different perspectives and cultures bring to an organization.

Additional Responsibilities Unique to this Position

Technical Skills:

Advanced Python
Databricks, Pyspark
Advanced SQL, ETL tools
Power Automate
Power Apps
SharePoint
GITLAB
Power BI
Jira
Mendix
Statistics

Soft Skills:

Strong problem-solving and analytical abilities.
Excellent communication and stakeholder management skills.
Proven ability to lead a team.
Strategic thinking
Advanced project management

Experience:

Intermediate level of relevant work experience required.
Please note that this is a Hybrid role

Role: Analytics Consultant

Industry Type: Industrial Equipment / Machinery

Department: Data Science & Analytics

Employment Type: Full Time, Permanent

Role Category: Business Intelligence & Analytics

Education

UG: Any Graduate

PG: Any Postgraduate

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