
Weekday
This role is for one of Weekday’s clients
Min Experience: 8 years
Location: Mumbai
JobType: full-time
Requirements
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.
Apply now
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