Principal Consultant - Data Solutions - Digital Transformation Consulting

About the MNC Consultancy

The company is getting into Digital Transformation business, which is still an unchartered area, worldwide

KEY AREAS :

- Data Architecture/ Data Scientist for marketing/ Marketing dashboards / Marketing command center creation

- Deep understanding of Data Driven marketing /Data specialist for CMP/Date Lake consulting

- Should be familiar with various

- DMPs (Adobe/IBM Marketing cloud/Lotame etc)

- Data Lakes (informatica/ Hortonworks / Pivotal etc).

- Having hands-on experience of various Martech tools and technology would be an added advantage

- The company feels that its own culture, flexibility, consumer understanding and risk-taking give us an edge on other traditional consulting firms.

- While Company will have employees dedicated to business consulting, it will also pool CEOs and leaders from across its advertising business and even outside getting the best of breed experts who have built businesses to create teams on a project-by-project basis.

- Its business model is a break from what clients have come to expect from traditional consultants, which charge clients for their time. It won't just advise on strategy, but it will also build products, campaigns, and infrastructure, with mantra of 'consultants that make'. Clients will see real results and business model is also tuned around delivering results. In the long run, it may take a share of revenue from the upside.

- It will bring out a fresh approach in the consulting industry by having entrepreneurs/ business leaders (within & outside the company) as Subject Matter Experts who have executed and created real business success rather than pure-play consultants. Clients will see them working as execution partners, pushing their teams and making things happen.

- It will be hands on approach where company will get its own hands dirty. Besides clients will see depth of knowledge from folks who are true digital business leaders & entrepreneurs. 

Key focus areas for the company :

- Growth Consulting for companies (promoter workshops, promoter coach, organisation transformation, organization growth, Digital Business turnarounds inside large companies etc)

- AI & Big Data (Data strategy, Org transformation with AI, AI tools and implementations, marketing command centers, Customer value exchange etc.)

- Marketing Transformation /CRM Consulting (Martech consulting/ data driven marketing)

- Innovation (Blockchain, IOT, Creative strategy, content strategy, Transmedia, Setting up startup accelerators, business on cloud, future of work, new digital businesses etc)

Experience / Exposure :

Job Objectives :

1. Achieve excellence in data architecture and engineering consulting engagements

2. Support successful sales, pre-sales and marketing activities

3. Support excellent relationships with technology partners

Responsibilities :

Delivery :

- Take lead during data architecture and engineering consulting engagements

- Develop and execute programme / project delivery plans for implementation of solutions

- Understand how people, process, technology and data work in concert forming operating models to enable data science teams

- Assist to identify opportunities for on-sell opportunities during consulting engagements

Business Development :

- Support responses to RFI/Qs from clients

- Support pre-sales activities with clients

- Develop proposed data architectures and operating models to meet client requirements

- Estimate effort and costs in delivering required data operating model for clients

- Assist in determining where partner solutions overlap with client requirements

Data architecture and engineering :

- Stay abreast of technology products / services in the data and analytics space

- Advise delivery teams how best to deploy solutions

- Develop working prototypes in lab or cloud infrastructures

- Develop white papers and other thought leadership

Key Skills :

Delivery :

- Project and programme management

- Architecture and implementation

- Service Management

- Influencing skills (managing client and leadership in technical decisions)

- Explaining very technical topics to non-technical audiences

Technology and methodologies

- Cloud implementation of data solutions (Google, AWS, Azure)

- Big data platforms - MapR, Hadoop (HortonWorks / Cloudera)

- Data Governance and Management platforms (Informatica, Collibra)

- Analytics tools (SAS, Tableau, Python)

- Graph and No-SQL databases (MongoDB, etc)

Data models :

- Relational, graph and semantic data modelling (appreciation for all, with deep knowledge in one)

- Relational data base and warehouse design

- Information flow analysis (requirements, KRIs/KPIs, DQ controls, etc)

- FIBO (Financial Information Business Ontology)