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We are seeking an experienced and visionary Practice Lead – Data Engineering to build, scale, and lead our Data Engineering practice as a strategic capability within the organization. This role is a key investment aligned with our long-term growth strategy, recognizing data as a foundational pillar for digital transformation, analytics, AI/ML, and enterprise decision-making. The Practice Lead will be responsible for defining the technical vision, delivery standards, talent strategy, and commercial roadmap for the Data Engineering practice. While current engagements span platforms such as Azure Data Factory, Microsoft Fabric, Synapse Analytics, Microsoft Purview, Power BI, and enterprise integration projects, the role is technology-agnostic and forward-looking, with a mandate to continuously evolve the practice in line with market trends and client needs. This role combines deep technical expertise, delivery governance, people leadership, and business acumen, and will act as a trusted advisor to both clients and internal leadership.
Job Responsibility:
Define and own the Data Engineering practice roadmap, including technology direction, service offerings, accelerators, and reusable frameworks
Continuously evaluate emerging platforms, architectures, and tools across cloud and open-source ecosystems (Azure, AWS, Fabric, Databricks, Snowflake, etc.)
Establish the practice as a Center of Excellence (CoE) for data ingestion, transformation, governance, and analytics enablement
Align practice goals with organizational growth objectives, client demands, and industry trends
Act as the technical authority for all data engineering engagements across the organization
Define reference architectures, design standards, and best practices for: Data lakes, lakehouses, and warehouses
Metadata management, lineage, and governance
Data quality, observability, and performance optimization
Batch and real-time data pipelines
Review and guide solution designs across projects to ensure scalability, security, and maintainability
Provide oversight across multiple client engagements to ensure consistent delivery quality
Define and enforce engineering practices including: Coding standards and reviews
Pipeline testing and validation
CI/CD for data workflows
Documentation and knowledge management
Conduct periodic technical health checks and delivery audits to proactively identify risks and improvement areas
Partner with Delivery Managers and Architects to resolve complex delivery challenges
Act as a trusted technical advisor for clients on data strategy, modernization, and platform adoption
Support pre-sales activities including solutioning, estimations, proposals, and client presentations
Translate business requirements into scalable data architecture and implementation approaches
Help clients move from traditional reporting to modern, data-driven decision-making platforms
Define skill matrices, learning paths, and certification plans for the practice
Mentor senior engineers and groom future practice leaders and architects
Foster a culture of engineering excellence, ownership, and continuous learning
Requirements:
About 12 to 15 years of experience in data engineering, analytics platforms, or large-scale integration programs
At least 5 years in a senior technical leadership, architecture, or practice-building role
Proven experience building and scaling enterprise-grade data platforms
Azure Data Factory, Synapse Analytics, Microsoft Fabric
Data governance tools such as Microsoft Purview
BI platforms like Power BI
Broad exposure to data engineering concepts: ETL/ELT, streaming, and event-driven pipelines
Data lakehouse and warehouse architectures
Data quality, lineage, security, and compliance
Experience across cloud platforms (Azure preferred
AWS exposure is a plus)
Familiarity with DevOps, CI/CD, and Infrastructure-as-Code for data platforms
Strong stakeholder management and executive communication skills
Ability to balance technical depth with business and commercial considerations
Experience working with multiple clients and managing competing priorities
Strategic mindset with a bias for execution and measurable outcomes