Manager Data Engineering

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).