We are seeking an experienced Director Data Engineering & Enterprise Transformation to lead our global Data Engineering function while remaining actively involved in technical design, architecture, coding, and modernization initiatives. This is not a traditional people management or program management role. We are looking for a leader who can balance strategic leadership with hands-on engineering, driving enterprise-scale transformation while mentoring a high-performing engineering team.

You will own the organization's data engineering strategy, cloud modernization roadmap, automation initiatives, and enterprise data platform, partnering closely with Technology, Finance, and Business leaders to deliver scalable, cloud-native solutions.

Key Responsibilities Leadership & Delivery Lead, mentor, and develop a high-performing Data Engineering team across multiple time zones. Manage, coach, and performance-review a team of 610 Data Engineers, Data Architects, and Software Engineers. Drive hiring, succession planning, and technical capability development.

Foster a culture of ownership, accountability, engineering excellence, and continuous improvement. Data Engineering & Architecture Design and implement scalable enterprise data architectures. Develop and optimize ELT/ETL pipelines and contemporary data platforms.

Lead migration from legacy systems to cloud-native architectures. Design robust data models, integrations, and automation frameworks. Establish enterprise architecture standards and best practices. Hands-on Engineering Actively contribute as an Individual Contributor (IC)



by writing and reviewing production-quality code.

Build and optimize SQL queries, Python services, ELT pipelines, and workflow orchestration. Review code, mentor engineers, and enforce engineering standards. Drive CI/CD, DataOps, observability, security, and platform reliability.

Enterprise

Transformation & Automation Lead enterprise modernization and digital transformation initiatives. Eliminate technical debt through platform modernization. Identify and automate manual business processes. Define governance, data lineage, auditability, and compliance standards. Deliver measurable improvements in efficiency, cost optimization, and operational excellence.

Stakeholder Management

Partner with Technology, Finance, Operations, and Executive Leadership. Present technical strategies, risks, and business outcomes to senior executives. Manage vendors, budgets, and technology investments. Translate business objectives into scalable engineering solutions.

Required Qualifications Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field. 10 years of experience in Data Engineering, Data Platform Engineering, Cloud Engineering,



or Enterprise Data Architecture. Minimum 5 years of engineering leadership experience, including directly managing a team of at least 610 Data Engineers, Data Architects, or Software Engineers. Proven experience leading distributed/global engineering teams across multiple time zones.

Demonstrated recent hands-on Individual Contributor (IC) experience in Data Engineering, with active involvement in designing, developing, and reviewing production-grade data solutions. Ability to balance technical execution with people leadership; this is not a pure people-management or program management role. Expert-level SQL experience.

Strong hands-on experience with Python (Scala is a plus). Extensive experience with Azure Data Factory. Strong experience with Snowflake. Hands-on experience with ELT/ETL tools such as dbt, Airflow, or Dagster.

Experience with Azure, AWS, or GCP. Strong understanding of CI/CD, containerization, orchestration, and automation. Demonstrated success modernizing legacy platforms and reducing technical debt.

Experience implementing DataOps, observability, governance, lineage, and platform reliability. Excellent communication skills with the ability to engage technical teams and executive stakeholders.

Preferred Qualifications Experience in Financial Services, Accounting, BPO, SaaS, or Enterprise Technology environments. Knowledge of accounting workflows, ERP integrations, and shared services.

Experience building internal developer platforms or self-serv .

📌 Director Data Engineering & Transformation | Remote (India)
🏢 CogentHub
📍 India