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8.0 - 12.0 years

4 - 24 Lacs

Mumbai, Maharashtra, India

On-site

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This role is for one of Weekday's clients Min Experience: 8 years Location: Mumbai JobType: full-time About the Role We are looking for a highly skilled and results-driven Assistant Vice President Data Engineering to join our Data & Analytics leadership team. In this role, you will be responsible for building, optimizing, and scaling data pipelines, architectures, and data processing systems. You will work closely with cross-functional teams to deliver robust, secure, and high-performing data solutions that support business intelligence, advanced analytics, and decision-making across the organization. This is a high-impact leadership position, ideal for someone who brings deep technical expertise in Data Engineering , especially around tools like Databricks , PySpark , and SQL , and can lead enterprise-grade data workflow development in a complex, fast-paced environment. Key Responsibilities Team Leadership & Strategy: Lead a team of data engineers, ensuring best practices in data development, documentation, and collaboration. Contribute to strategic decisions related to data infrastructure, architecture, and tooling. Data Pipeline Development: Design and implement highly scalable and efficient data pipelines for both batch and real-time use cases using Databricks , PySpark , and other big data tools. ETL & Data Workflow Management: Build and manage robust ETL processes that support data transformation, cleansing, enrichment, and ingestion across multiple data sources and platforms. SQL Development: Write optimized, complex SQL queries for large datasets, ensuring data integrity and performance efficiency. Architecture & Integration: Collaborate with data architects to ensure scalable and secure integration of data systems across cloud and on-premise environments. Data Governance & Quality: Work closely with data governance and compliance teams to ensure adherence to data quality standards, security protocols, and regulatory guidelines. Collaboration & Stakeholder Engagement: Partner with business stakeholders, data scientists, and analysts to understand data requirements and deliver timely, accurate, and accessible data solutions. Continuous Improvement: Evaluate emerging technologies, recommend new tools, and lead proof-of-concept initiatives to continually improve data engineering capabilities. Required Skills and Experience 8+ years of progressive experience in Data Engineering , including at least 2 years in a leadership or managerial role. Proficiency in SQL with a deep understanding of query optimization and data modeling. Hands-on experience with Databricks , PySpark , and big data processing frameworks. Strong understanding of data workflows , orchestration tools, and data integration methodologies. Experience working with cloud platforms such as Azure , AWS , or GCP . Proven track record in developing scalable and maintainable data pipelines and workflows. Strong communication skills and the ability to work effectively with both technical and non-technical stakeholders. Familiarity with CI/CD for data pipelines, monitoring tools, and version control systems like Git. Preferred Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Certification in Databricks , Azure Data Engineer , or similar platforms is a plus. Exposure to data mesh or data lakehouse architecture is advantageous.

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