Senior Data Engineer

Required Skills

• Hands on experience in SQL ,Python, Pyspark, ETL development, Azure Data Factory and Power BI knowledge and Hands-on experience
• Implementation experience of GenAI technologies.
• Experience managing cross-functional technical teams and coordinating delivery across analytics, development, and AI tracks.
• Strong communication and stakeholder management skills.
• Working knowledge of cloud environments and API-based solution design.
• 4+ years of experience in analytics, data engineering, or application development, with at least 2 years in a leadership or project management capacity.
• Exposure to AI/ML development lifecycles and integration into analytics/engineering platforms.
• Experience working in agile environments with sprint planning, retrospectives, and release management.
• Understanding of data architecture, CI/CD for analytics, and version control systems (Git).

Role & Responsibilities:

Project & Execution Management

• Translate business problems into structured data engineering and analytics solutions.
• Prioritize workloads, manage dependencies, and track progress to ensure timely, high-quality deliverables.
• Implement scalable processes for data validation, governance, and version control.
• Proficient in understanding the Business Requirement and converting it into process flows and codes (Special preference for SQL based stored procedures)

Team & Delivery Leadership

• Manage the full data engineering and analytics delivery lifecycle from requirement definition and data design to solution deployment and communication.
• Ensure alignment between business needs, data capabilities, and technical execution.
• Promote collaboration, agile delivery, and continuous improvement within the team.

Stakeholder Management

• Collaborate closely with product owners, business stakeholders, and internal teams to understand goals and translate them into actionable engineering and analytics initiatives.
• Present insights, solution proposals, and progress updates in a clear, business-friendly manner.

Innovation & Capability Building

• Encourage adoption of modern data technologies and AI frameworks within the team.
• Identify opportunities to automate manual processes and improve data workflows.
• Keep abreast of emerging analytics tools, MLOps practices, and AI trends to enhance team capabilities.

Required Qualifications

• Bachelors degree in computer science, Data Science, Engineering, or a related discipline.
• Preferred certifications in Azure Data engineering and GenAI technologies.