Data Practitioner

About the Role

We are looking for an experienced Data Practitioner to lead and deliver data-driven transformation initiatives for global enterprise clients. The role requires a strong combination of data strategy, data engineering, analytics, cloud, AI/ML, and client consulting expertise.

The ideal candidate will work closely with business and technology stakeholders to define data strategies, build modern data platforms, enable advanced analytics, and translate complex data challenges into measurable business outcomes.

Key Responsibilities

• Lead end-to-end data transformation engagements across strategy, architecture, engineering, analytics, and AI/ML.
• Partner with CXOs, business leaders, and technology teams to identify high-value data and analytics use cases .
• Define and implement enterprise data strategies, operating models, and roadmaps .
• Drive modernization of legacy data environments into cloud-native and modern data platforms .
• Provide expertise across Data Engineering, Data Warehousing, Data Lakes/Lakehouse, BI, Analytics, AI/ML, and Data Governance .
• Lead large-scale data programs involving multiple technology and business stakeholders.
• Develop solutions using cloud platforms such as AWS, Microsoft Azure, or Google Cloud .
• Work with technologies such as Snowflake, Databricks, Microsoft Fabric, BigQuery, Spark, Kafka, Python, SQL, and modern BI platforms .
• Establish data governance, quality, security, privacy, and master-data practices.
• Identify opportunities to leverage Generative AI, AI/ML, and advanced analytics to create business value.
• Build and mentor high-performing data and analytics teams.
• Collaborate with sales and consulting teams on pre-sales, solutioning, proposals, RFPs, and client presentations .
• Contribute to account growth by identifying new opportunities and expanding existing data transformation engagements.
• Develop thought leadership, accelerators, frameworks, and reusable data solutions.

Required Experience & Skills

• 8–15+ years of experience in Data, Analytics, Data Engineering, or Digital Transformation .
• Strong experience delivering enterprise-scale data transformation programs.
• Excellent understanding of modern data architecture and cloud data ecosystems .
• Hands-on or strong working knowledge of SQL, Python, Spark and data engineering technologies .
• Experience with one or more major cloud platforms: AWS, Azure, or GCP .
• Strong understanding of Data Governance, Data Quality, Metadata Management, MDM, and Data Security .
• Experience with modern data platforms such as Snowflake, Databricks, BigQuery, Microsoft Fabric , or equivalent.
• Strong stakeholder and client management skills.
• Ability to translate business problems into scalable technology and data solutions.
• Experience managing large teams and complex, multi-workstream programs is preferred.
• Strong communication, presentation, consulting, and problem-solving capabilities.

Preferred Experience

• Experience working with Fortune 500 / large enterprise clients .
• Experience across industries such as BFSI, Manufacturing, Retail, Telecom, Energy, or Technology .
• Experience in GenAI, AI/ML, Data Products, Data Mesh, or Lakehouse architecture .
• Consulting or IT services background with exposure to business development and pre-sales .
• Relevant cloud/data certifications are an advantage.

What Success Looks Like

• Successful delivery of large-scale data transformation programs.
• Strong executive-level client relationships.
• Creation of measurable business value through data and analytics.
• Growth of data transformation opportunities within strategic accounts.
• Development of scalable data capabilities, platforms, and high-performing teams.
• Establishment of the organization as a trusted data and AI transformation partner for clients.

Ideal Candidate Profile

We are looking for a business-oriented data leader who combines strong technical depth with consulting and client-facing capabilities. The candidate should be comfortable moving between CXO conversations, data strategy, solution architecture, delivery leadership, and pre-sales , while building teams and driving measurable outcomes.