Manager, Data Hub Analyst/Engineer

Location

Mumbai | India

Job description

Together with analytics team leaders you will support our business with excellent data models to uncover trends that can drive long-term business results.

How you will contribute

You will:

• Work in close partnership with the business leadership team to execute the analytics agenda
• Identify and incubate best-in-class external partners to drive delivery on strategic projects
• Develop custom models/algorithms to uncover signals/patterns and trends to drive long-term business performance
• Execute the business analytics program agenda using a methodical approach that conveys to stakeholders what business analytics will deliver

What you will bring

A desire to drive your future and accelerate your career and the following experience and knowledge:

• Using data analysis to make recommendations to senior leaders
• Technical experience in roles in best-in-class analytics practices
• Experience deploying new analytical approaches in a complex and highly matrixed organization
• Savvy in usage of the analytics techniques to create business impacts

Responsibilities

AMEA region is one of the fastest growing regions for Mondel z with a revenue of $7B+ and 10K+ potential data analytics users. In this role, you will enable and drive the data strategy , analytics agenda and priorities for the India Business Unit (BU) within AMEA region, which is distinguished by its significant strategic importance and substantial scale. Data analytics is a critical enabler for growth across this BU and a key contributor in driving the global strategy and transformation towards an AI Enabled Enterprise.

• As a DA Data Hub Analyst and Engineer , you would be establishing the Data Strategy for India BU in support of the Analytics and AI/ML Agenda
• Establishing Data Management cross functional foundations (Quality, Process, SOP, critical data sets, playbook on data ingestion, etc)
• Own the Data Hub operations for India BU and assure optimal execution and continuous improvement with supporting teams and partners
• Expected to contribute as data expert to influence demand and solution shaping in collaboration with Data Scientists
• Creating data products prototypes (data models, architect etc) in collaboration with broader DA teams
• Analyze data to identify trends, patterns and insights, including visualizing data through dashboards and reports in order to communicate findings
• Establish data quality standards and processes to ensure accuracy, completeness and reliability of data and daily operations
• Develop playbooks for data ingestion, detailing steps for collecting, cleaning and loading of data in the most efficient manner

Experience

• Data engineering Data analyst experience, 8+ years
• Experienced in a full start-to-end DA tool rollouts (Raw data to ETL to Front end)

Skillsets requirement

Data analytics skills

Must have a good understanding of the concepts, methods and techniques used:

• Data management, for example data integration (ETL, pipelines) or metadata, including daily operations and support activities related to data enablement
• Data architecture , for example the difference between data warehouse, data lake or data hub.
• Data modelling, for creation of right reusable data assets, knowledge of Indicators (KPIs) and scorecards
• Data governance , for example MDM, data quality and data stewardship practices.
• Analytics , for example diagnostic, descriptive, predictive and prescriptive.
• Statistical skills , for example understanding the difference between correlation and causation.

• Project management, for example understanding project management principles and tools to effectively plan, execute and monitor deliverables

Technology skills

Good understanding of the tools and technologies in the DA team:

• Programming languages like SQL, Python or R and notebooks like R Studio or Jupyter.
• Data integration tools like Informatica or Talend.
• Analytics and Business Intelligence tools like Microsoft Power BI or Tableau.

Soft skills

• Communication , for example conveying information to diverse audiences in a way that is easily understood and actionable.
• Facilitation and conflict resolution , for example hosting sessions to elicit ideas from others, understand their issues and encourage group participation.
• Creative thinking and being comfortable with unknown or unchartered territories , for example framing new concepts for business teams and brainstorming with business users about future product and services.
• Teamwork , for example working with both business domain teams as well as DA teams and MDS stakeholders.
• Collaboration , for example fostering group problem solving and solution creation with business and technical team members.
• Relationship management , for example creating relationships and builds trust with internal and external stakeholders quickly.
• Storytelling , for example by creating a consistent, clear storyline for better understanding
• Influencing , for example by asserting ideas and persuading others to gain support across an organization or to adopt new behaviors.

Domain skills

Must have a good understanding of the business process and associated data:

• Business Acumen , for example understanding business concepts, practices and business domain language to engage in problem solving sessions and discuss business issues in stakeholder language.
• Business Process Transformation , for example ability to understand how DA can help redesign the way work is done.
• Business data, for example the structure, ownership and use within an organization

Other skills

• Agility, Growth mindset will be crucial
• Project management capabilities including ability to manage risks , for example understanding of project management concepts to organize their own work and the ability to collaborate with project managers to align business expectations with the DA team delivery capabilities.
• Vendor negotiation and effort estimation skills, for example to manage the right partner skills at right cost based on the complexity and importance of the initiatives to be delivered or supported
• Business case development , for example to help develop support for the experimenting selected use cases or measure the impact/business value created.
• Decision modelling , for example, supports decision makers and improves complicated decisions that involve trade-offs among alternative courses of action by using decision-problem models.
• UX/design , for example by creating products and visualizations that are easy to work with and support the activities required by the end users.

Job tags

Salary