Data & Advanced Analytics AI Practice Lead

Location: Hyderabad, India

Employment Type: Full-time

Data & Analytics Cloud Data Platforms Lakehouse BI & Visualization AI / ML Practice Leadership

KEY RESPONSIBILITIES

• Define and drive the strategy, offerings, and roadmap for Tachyon’s Data & Advanced Analytics practice.
• Own practice-level revenue and growth targets, working closely with sales and account teams to build and convert pipeline.
• Build out team structure and hiring plans, and help recruit, mentor, and retain data engineers, analytics consultants, and architects.
• Develop reusable accelerators, frameworks, and reference architectures that differentiate Tachyon in client pursuits.
• Define the go-to-market approach and partnerships (cloud hyperscalers, data platform vendors) that strengthen the practice.
• Serve as lead architect for data platform, data warehousing, data lake, and lakehouse engagements across cloud environments such as  Azure, AWS, or GCP.
• Design and oversee analytics and BI solutions, including reporting, dashboards, and self-service analytics using tools such as Power BI or Tableau.
• Architect advanced analytics, machine learning, and AI / GenAI solutions, and guide delivery teams on implementation best practices.
• Define data governance, data quality, security, and MDM approaches appropriate to each client’s environment.
• Review and approve technical designs across the practice’s active engagements, and act as an escalation point for complex delivery issues.
• Lead technical discovery with prospective clients to understand current-state data maturity and define target architecture.
• Support proposals, RFP responses, solution estimation, and effort sizing for Data & Advanced Analytics opportunities.
• Run or oversee POCs and technical demonstrations that showcase the practice’s capabilities.
• Represent Tachyon in client workshops, architecture reviews, and executive-level conversations with client CTOs, CDOs, and analytics

• leadership.
• Coach and upskill architects and consultants within the practice on modern data and AI technologies.
• Stay current on emerging trends in data platforms, advanced analytics, and AI, and translate them into practical offerings.
• Contribute to internal training, case studies, and external thought leadership that raises the practice’s visibility.

REQUIRED QUALIFICATIONS

• Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s preferred.
• 12+ years in data engineering, analytics, or data architecture — including several years as a practice lead, architect, or senior technical
• leader, ideally within an IT services or consulting organization.
• A career spanning traditional BI, Data Warehousing, and Analytics architecture (Teradata, Oracle, SAP BW/HANA, Informatica, SSIS) that
• has since evolved into modern cloud data platforms, lakes / lakehouses, and advanced analytics.
• Deep hands-on expertise across data warehousing, data lakes / lakehouses, ETL / ELT pipelines, and modern data platforms.
• Strong experience with at least one major cloud platform (Azure, AWS, or GCP) and its native data and analytics services.
• Working knowledge of BI and visualization tools (Power BI, Tableau) and big-data frameworks (Spark, Databricks).
• Experience building or scaling a practice or capability area — team growth, offering development, and revenue accountability.
• Strong client-facing skills, including pre-sales, proposal development, and executive communication with client CTOs, CDOs, or analytics leadership.

PREFERRED QUAL I F ICAT IONS

• Exposure to AI / ML and Generative AI solution design, including LLM-based applications and MLOps practices.
• Cloud or data-platform certifications (Azure Data Engineer, Azure Solutions Architect, AWS Data Analytics, or Databricks).
• Experience serving enterprise clients across industries within an IT services model — ideally spanning US, Canada, Middle East, or other global markets.
• Familiarity with data governance and compliance frameworks relevant to enterprise clients.

TECHNICAL SKILLS

• Platforms: legacy / enterprise BI & DW — Teradata, Oracle, SAP BW/HANA, Informatica, SSIS, Cognos, MicroStrategy, Business Objects, or Qlik.
• Cloud data: modern data & warehousing — Snowflake, Databricks, Synapse, Redshift, BigQuery, or equivalent.
• Data engineering: SQL, Python, Spark, and orchestration tools such as Airflow or ADF.
• Analytics & AI: Power BI, Tableau, or equivalent enterprise reporting tools; ML frameworks and Generative AI / LLM tooling.