
Associate Director
- Bangalore, Karnataka
- Permanent
- Full-time
- Leadership & Strategy: Define and execute the organization’s data engineering strategy aligned with business objectives. Establish best practices for architecture, data governance, and platform modernization with a focus on GCP services.
- Data Platform Ownership: Lead the design, development, and management of cloud-native data platforms on GCP, leveraging tools such as BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Vertex AI integrations.
- Architecture & Scalability: Drive end-to-end data architecture decisions to ensure scalability, performance, and security. Evaluate emerging technologies and recommend their adoption to keep the data ecosystem future-ready.
- Team Management: Lead and mentor a team of senior data engineers, architects, and analysts. Build capabilities through training, knowledge sharing, and fostering a culture of innovation and excellence.
- Collaboration & Stakeholder Management: Partner with product, analytics, business, and technology teams to translate business requirements into scalable data solutions. Act as the bridge between leadership and engineering teams.
- Data Governance & Compliance: Ensure data quality, lineage, and compliance with regulatory standards. Establish policies around metadata management, data lifecycle, and secure data access.
- Innovation & Transformation: Drive modernization of legacy data systems by migrating to GCP-based architectures. Promote automation, AI/ML adoption, and advanced analytics to unlock new business insights.
- Operational Excellence: Establish SLAs, monitoring frameworks, and incident management processes for reliable data delivery pipelines.
- Experience: 15–20 years of progressive experience in data engineering, with at least 5+ years in leadership roles overseeing large-scale data platforms.
- Technical Expertise: Deep understanding of Google Cloud Platform (GCP) and its ecosystem – including BigQuery, Dataflow, Dataproc, Cloud Composer, Pub/Sub, Cloud Functions, Cloud SQL, and Looker.
- Data Engineering Tools: Strong proficiency in data pipeline development, real-time streaming, ETL/ELT, orchestration, and advanced SQL.
- Programming Skills: Expertise in Python, Java, or Scala for data engineering workloads.
- Architecture Skills: Strong background in distributed systems, microservices, data lakes, data warehouses, and API-driven integrations.
- Leadership: Proven ability to lead large, cross-functional teams and deliver enterprise-wide data transformation initiatives.
- Industry Knowledge: Experience working with complex, large-scale datasets in industries such as BFSI, healthcare, retail, or technology.
- Soft Skills: Excellent communication, strategic thinking, stakeholder engagement, and change management abilities.
- Certification in Google Cloud Professional Data Engineer or Cloud Architect.
- Experience with machine learning pipelines and integration of AI-driven solutions.
- Exposure to multi-cloud or hybrid-cloud environments.