Director - Data Engineering

We are looking for a Director - Data Engineering to lead the data engineering strategy, architecture, and execution for a large-scale consumer-facing platform. The ideal candidate will have strong experience building and scaling modern data platforms that power customer-facing products, personalisation, analytics, experimentation, recommendations, and business intelligence. This role requires a strong combination of technical depth, data architecture expertise, engineering leadership, and stakeholder management, with hands-on experience across GCP-based modern data ecosystems.

Responsibilities:

• Define and drive the enterprise data engineering strategy and roadmap aligned with business and product objectives.
• Architect and scale highly available, secure, and cost-efficient GCP data platforms capable of handling large-scale consumer data.
• Lead data engineering teams responsible for batch and real-time data pipelines, data platforms, data products, and analytics infrastructure.
• Design and implement modern data architectures across data lake, data warehouse, lakehouse, streaming, and analytical platforms.
• Drive adoption of GCP services such as BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Storage, Composer, Cloud Functions and related services.
• Build robust data pipelines integrating data from customer, product, transaction, marketing, operational, and third-party systems.
• Partner closely with Product, Engineering, Analytics, Data Science, ML, Marketing, and Business teams to build data products that directly impact the customer journey.
• Enable data capabilities for personalisation, recommendation, search, customer segmentation, experimentation, customer analytics, and real-time decisioning.
• Establish strong standards around data quality, governance, lineage, security, privacy, observability, and reliability.
• Drive modernisation of legacy data platforms and migration toward scalable cloud-native architectures.
• Establish engineering best practices around CI/CD, automated testing, monitoring, performance optimisation, and infrastructure automation.
• Optimise data platform performance and cloud costs at scale.
• Mentor and develop senior engineering leaders and build a high-performing data engineering organisation.
• Influence senior leadership and stakeholders on data strategy, architecture, investment priorities, and technology decisions.

Requirements:

• 14-18 years of overall experience in Data Engineering / Data Platforms / Data Architecture.
• Strong experience leading large-scale data engineering teams and organisations.
• Proven experience building and scaling consumer-facing B2C/D2C platforms with significant transaction, customer, or behavioural data volumes.
• Strong hands-on expertise with Google Cloud Platform (GCP).
• Deep experience with BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, Composer/Airflow or equivalent GCP data services.
• Strong understanding of data lake, data warehouse, lakehouse and modern data platform architectures.
• Experience with both batch and real-time/streaming data pipelines.
• Strong programming experience in Python, Java, or Scala.
• Strong knowledge of SQL, distributed systems, data modelling, ETL/ELT and data processing frameworks.
• Experience designing highly scalable and reliable data systems handling millions of customers / high-volume consumer data.
• Strong understanding of data governance, security, privacy, data quality, lineage and observability.
• Excellent stakeholder management skills with the ability to work with C-level executives, Product, Engineering, Data Science and Business leadership.

Strongly Preferred:

• Experience in high-scale consumer businesses such as E-commerce, Marketplace, FinTech, Travel, Mobility, FoodTech, Retail, Media or Internet platforms.
• Experience supporting personalisation, recommendations, search, customer 360 experimentation and real-time analytics.
• Experience with Kafka, Spark, Databricks, Snowflake or other modern data technologies.
• Exposure to ML/AI data platforms and MLOps.
• Experience driving 01 data platform initiatives as well as large-scale platform modernisation.
• Experience managing multiple engineering managers / senior technical leaders.

Leadership Expectations:

• Strong people leadership and organisational building capabilities.
• Ability to balance strategic thinking with technical depth.
• Strong ownership mindset with a bias toward execution.
• Excellent communication and influencing skills.
• Ability to simplify complex data architecture and communicate effectively with business and technology leadership.
• Strong focus on building scalable, reliable, secure and business-impactful data platforms.
• B. Tech / BE / MCA / equivalent technical qualification from a reputed institution preferred.

What Success Looks Like:

• A scalable and future-ready GCP data platform supporting the organisation's consumer ecosystem.
• Faster and more reliable access to high-quality data across Product, Engineering, Analytics and Business teams.
• Stronger real-time data capabilities for personalisation, recommendations and customer experiences.
• Improved data quality, governance, reliability and platform cost efficiency.
• A high-performing data engineering organisation with strong technical leadership and execution capabilities.

Skills

BigQuery, Dataflow, GCP, Google Cloud Platform