- We are looking for an experienced and hands-on Project Manager in Data Engineering who can lead the end-to-end delivery of data pipeline projects across Azure and AWS environments. The ideal candidate will bring strong technical depth in data engineering along with client-facing and project execution capabilities.
Key Responsibilities
· Lead and manage multiple data engineering projects across Azure and AWS ecosystems.
· Gather client requirements and translate them into technical specifications and delivery roadmaps.
· Design, oversee, and ensure successful implementation of scalable data pipelines, ETL processes, and data integration workflows.
· Collaborate with internal data engineers, BI developers, and client stakeholders to ensure smooth project execution.
· Ensure adherence to timelines, quality standards, and cost constraints.
· Identify project risks, dependencies, and proactively resolve issues.
· Own the client relationship from initiation to delivery – conduct regular check-ins, demos, and retrospectives.
· Stay updated on emerging tools and best practices in the data engineering space and recommend their adoption.
· Lead sprint planning, resource allocation, and tracking using Agile or hybrid methodologies.
Requirements
· 7–10 years of total experience in data engineering and project delivery.
· Strong experience in Azure Data Services – Azure Data Factory, Synapse, Databricks, Data Lake, etc.
· Working knowledge of AWS data tools such as Glue, Redshift, S3, and Lambda functions.
· Good understanding of data modeling, data warehousing, and pipeline orchestration.
· Experience with tools such as Talend, Airflow, DBT, or other orchestration platforms is a plus.
· Proven track record of managing enterprise data projects from requirement gathering to deployment.
· Client-facing experience with strong communication and stakeholder management skills.
· Strong understanding of project management methodologies and tools (e.g., JIRA, Trello, MS Project).
