Data Engineering Practice Head

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Lead our Data Engineering, BI & Analytics, and AI/ML practices with end-to-end accountability from devising data platforms and pipelines to delivering business insights and embedded intelligence. Align strategic direction and technical execution to drive transformation and innovation across the organization.
Key Responsibilities

• Strategic Leadership & Practice Building
• Define and execute a unified vision for Data Engineering, BI, Analytics, and AI/ML.
• Cultivate a high-performance team hire, scale, onboard, and mentor engineers, data scientists, and analytics professionals.
• Evangelize data best practices, AI ethics, and analytics culture across business units and executive audiences .
• Data Architecture & Engineering
• Architect scalable, secure, and cost-efficient data platforms and lakes/warehouses using technologies like Spark, Kafka, DBT, Airflow, Snowflake, Redshift, Databricks, etc. .
• Oversee design, implementation, and optimization of ETL/ELT pipelines (batch & streaming) to support analytics and AI/ML workloads .
• Implement data governance: ensure lineage, metadata management, quality controls, privacy, and regulatory compliance .
• Analytics & Intelligence
• Partner closely with analytics and BI leads to define requirements, generate dashboards and self-serve tools, and drive adoption of data-embedded decisioning platforms .
• Support analytics and BI with robust data delivery, data models, and data product pipelines.
• AI/ML Enablement
• Enable the AI/ML lifecycle by engineering feature stores, automated feature pipelines, and model-ready data environments .
• Collaborate with ML engineers/data scientists to transition models into production, ensure traceability, and optimize inference operations .
• Maintain data platforms for real-time, NLP, forecasting, and other AI use cases .
• Stakeholder Engagement & Governance
• Act as a trusted advisor to senior leadership, translating business needs into technical roadmaps and measurable KPIs .
• Communicate trade-offs, manage expectations, and resolve data-related risks including biases, ethics, security, and compliance .
  

Experience & Qualifications

• Leadership: 10 15+ years in data engineering or analytics; minimum 5+ years in leadership roles (manager/lead/director).
• Technical: Hands-on with Python/SQL/Java, distributed systems (Spark, Kafka), cloud-native tools (AWS/Azure/Google Cloud Platform), data orchestration (Airflow, DBT), and data storage (Snowflake, Redshift, BigQuery).
• Data Governance: Proven skill in metadata, lineage, data security, privacy regulations (GDPR, HIPAA etc.).
• AI/ML Exposure: Experience deploying pipelines for ML/AI use cases and supporting feature engineering, realtime inference.
• BI/Analytics: Ability to collaborate with BI teams, enabling self-serve analytics and impactful dashboarding.
• Soft Skills: Exceptional communication, strategic thinking, stakeholder influencing, and cross-functional collaboration .
• Education: Degree in Computer Science, Engineering, Data Science or equivalent. Advanced degrees or certifications preferred.
  

Ideal Traits & Impact

• Visionary thinker driving continuous data-driven transformation.
• Able to simplify complexities and present clear, business-aligned strategies.
• Culture catalyst encouraging innovation, learning, and ethical data usage.
• A tech-savvy diplomat who balances strategic leadership with solution-level oversight and mentorship.
  

Why This Role Matters

• AI leadership roles are proliferating. Beyond technical oversight, the Practice Head ensures ethical and risk-aware AI adoption blending deep tech acumen with regulatory, governance, and business alignment .
• With Data Engineering and BI as the enterprise s data engine, and AI/ML as its intelligence layer, this role is pivotal for unlocking new efficiencies, revenue streams, and competitive advantage.

Seniority level

• Seniority level

  Director

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Software Development

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