Data Analytics Team Leader

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