▷ Immediate Start: Data Product Manager
3 weeks ago
At Airtel Digital, we are transforming from a telecom giant to a digital force and changing how people consume entertainment, how companies manage their assets to how cities use energy.. Today, our work goes beyond telecom -- we build products that entertain and inform, connect devices to the internet, and enable businesses to securely harness the power of their data.
Role - Data Product Manager
About the Position
At Airtel, the data platform is at the heart of how the business operates. We process 2 trillion events daily and host 100 PB of data. This powers all business and functions across Airtel. Today, the businesses are more data hungry than ever and use cases are ever evolving. To solve this, we need to innovate to make our data platforms self-serve and scalable in every possible way.
As a Data product manager, you would be responsible for developing capabilities that will have customer problems at its heart. You should be able to break down big complex problem statements into smaller addressable units, can think future-proof solutions for each unit, and execute to high standards of quality. You will work on platforms that are highly modular and scalable in usage. At the same time, you should also be responsible in defining customer back shippable capabilities so that the value to the customer and business is delivered frequently and consistently. – Be agile to deliver, fail fast and recover.
Your stakeholders include but not limited to – Engineering, Business & Marketing, Analytics, Customer experience teams, Product teams of Channels and platforms. In some of the cases, the stakeholders might extend to Finance and Regulatory teams as well. In short, coordination and managing the stakeholders across functions is one of the key area you should be excelling in.
Preferred Skills
An ideal candidate for the Data Product role should have the following experience for at least 2 years-
- The candidate should have a strong understanding of data strategy, governance, and data management principles. They should be able to define data governance frameworks, establish data standards, and ensure compliance with data regulations- Have a working understanding of the Data Mesh concept and its principles. They should be familiar with the decentralized data architecture, domain-oriented approach, and data product thinking concepts- The candidate should have experience in product or services focused on data. They should be able to define data product roadmaps, prioritize features, and work closely with cross-functional teams to deliver valuable data products- Strong analytical skills are helpful for the Data Product Manager to derive insights from data and make data-driven decisions. They should be able to work with Analytics team to generate the applicable Insights from the data for the business- Candidates should be able to work with various stakeholders, including domain owners, data engineers, data scientists, Program managers and business teams, to understand requirements, align priorities, and drive successful data product initiatives- The Data Product Manager may not be responsible for hands-on coding, they should have a working technical understanding of data technologies, data architecture, and data integration concepts. This will enable them to effectively collaborate with technical teams and make informed decisions- Should be adaptable and willing to explore new technologies and approaches to data management and product development.- A strong business acumen and the ability to align data initiatives with business objectives. They should understand the value of data-driven decision-making and be able to articulate the business impact of data products.- Define data product requirements and drive execution with engineering, TPM, and other partner teams.- Identify the problem statements from the business and experience teams, break down the complexities into smaller units of capabilities, and drive this clarity across functions.- Liaison with other platform and channel product teams and deconstruct, stitch, and extend capabilities present in digital platforms in order to deliver value for the customer.- Make trade-off decisions based on technical and business insights and manage internal and external stakeholders- Have a strong bias to action on a day-to-day basis, and call out challenges in the right forums. Be open to feedback and be able to change directions quickly.- Adapt to the changing needs of the market and the organisation. Be conscious of the ecosystem, organisation strategies, and recommend the right course of action – call out trade-offs, but respect decisions.- Work with Product leadership to demonstrate the vision, update key milestones, or seek decisions. Your ability to communicate in a clear, crisp manner will go a long way in being successful in this role.
Preferred Qualifications:
- A computer science graduate or equivalent and hands-on experience in product development, as well as a technical understanding of data platform system design at scale. Having an MBA is a plus.- A deep understanding of data management, governance, observability, warehousing, and business intelligence technologies, with an inclination to experiment the products to experience the products first-hand- At least 2-3 years of experience as a data product manager, delivering successful data infrastructure platforms at scale.- Should be able to understand the customer pain points and business needs and articulate them to the cross functional teams so that the teams can work towards this common goal- Understanding of tech, architectural frameworks, data flows, and microservices that result in tech capacities.- Challenge the status quo, question the why, and get a deep understanding of the business and the products behind them.- An entrepreneurial mindset, end-to-end ownership of the product and work across stakeholders to achieve the desired objectives for the product.- Exceptional communication, collaboration and ability to evangelize the product or feature.- High affinity towards data driven decision making, and data driven insights. Should be able to convert data to insights, and insights to ideas.- Effective prioritization framework to focus on the right features and capability to ship.
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