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Job Description & How to Apply Below
Accordion is a global financial consulting and technology firm helping CFOs and their teams drive value creation. Rooted in private equity rigor and powered by data, analytics, and AI, we partner with companies across industries to turn insight into impact.
Accordion works at the intersection of Private Equity sponsors and portfolio companies’ management teams across every stage of the investment lifecycle. We provide hands-on, execution-oriented support, driving value through the office of the CFO by building data and analytics capabilities and identifying and implementing strategic work, rooted in data, analytics and AI.
Accordion is headquartered in New York City with 10 offices worldwide, including the India office
based out of Hyderabad. Join us and make your mark on our company.
Data & Analytics (Accordion | Data & Analytics)
Accordion's Data & Analytics (D&A) practice in India delivers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges.
We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics.
D&A team members deliver data and analytical solutions designed to streamline reporting capabilities and enhance business insights across vast and complex data sets ranging from Sales, Operations, Marketing, Pricing, Customer Strategies, and more.
Working at Accordion in India means joining 800+ analytics, data science, finance, and technology experts in a high-growth, agile, and entrepreneurial environment to transform how portfolio companies drive value. It also means making your mark on Accordion’s future—by embracing a culture rooted in collaboration and a firm-wide commitment to building something great, together.
Join us and experience a better way to work!
Location:
Hyderabad, Telangana
Role Overview :
The Lead Data Engineer at Accordion is responsible for architecting and maintaining modern, scalable data platforms that power analytics, AI, and decision-making across client organizations. This role demands deep expertise in cloud-native architectures including data lakes, lake houses, and enterprise data warehouses, to deliver robust, cost-optimized solutions addressing both current and future client needs.
The Lead Data Engineer will take an AI-first approach to every engagement, leveraging AI tools to
accelerate delivery, enhance productivity, and build data infrastructure that is architected to be AI ready from the ground up. A successful candidate will possess strong business acumen, cloud
platform expertise, and the ability to communicate effectively with cross-functional stakeholders to
drive end-to-end solution delivery.
What You will do:
Partner with client stakeholders to understand business challenges and translate them into data architecture requirements and actionable solution roadmaps.
Lead the design of cloud-native data platform architectures, including data lakes, lake houses (Delta Lake, Apache Iceberg), and modern data warehouses, recommending the right technology stack per engagement.
Collaborate with business and technology teams to define KPIs, data models, and metrics frameworks aligned with client goals.
Partner with Project Managers to develop and execute delivery plans ensuring high-quality output within agreed timelines.
Evaluate and lead the implementation of modern data integration patterns: streaming pipelines, ELT/ETL orchestration, and real-time data processing.
Design and lead the implementation of data infrastructure that is AI-ready by design: ensuring proper governance, lineage, and accessibility patterns that enable downstream AI and analytics consumption.
Responsibly integrate/leverage AI tools (Claude, Git Hub Copilot, Cortex, Genie, or similar) to accelerate pipeline development, code reviews, documentation, and solution delivery.
Design, build and deploy MCP (Model Context Protocol) servers to expose data platform capabilities as tools consumable by AI agents and LLM-powered workflows.
Conduct…
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