Senior Data Engineer

Overview

As Senior Data Engineer, you will design and run scalable data pipelines and architectures that power data-driven decisions. You’ll lead cross-functional data projects, mentor engineers, and uphold governance and security standards. This role blends hands-on pipeline work with leadership to ensure reliable, high-quality data delivery at scale. You’ll work with modern cloud-native tools to drive transformation and impact across client engagements.

Responsibilities

• Design, build, and maintain scalable data pipelines using SQL and Python, with Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and PySpark
• Lead integration of complex data systems ensuring data consistency across platforms
• Implement CI/CD practices for data pipelines to improve efficiency and quality
• Collaborate with data architects, analysts, and stakeholders to translate requirements into technical solutions
• Oversee and mentor a team of data engineers to deliver high-quality projects
• Develop and enforce data governance, security, and compliance practices
• Optimize data retrieval and develop dashboards and reports for business teams
• Continuously evaluate new technologies to enhance data engineering capabilities

Key requirements

• 3+ years of industry experience in data engineering
• Strong proficiency in SQL, Python, and big data technologies
• Experience with cloud-native orchestration tools and distributed processing
• Experience with Infrastructure as Code (Terraform)
• Solid understanding of CI/CD, DevOps/DevSecOps
• Proven leadership experience managing data engineering teams
• Excellent problem-solving in ambiguous environments
• Proficient with AI-assisted workflows to boost task efficiency
• Strong communication and interpersonal skills
• Understanding of data architecture (data mesh, data lake, data warehouse, data lakehouse)

• communication
• leadership
• problem-solving
• SQL
• Python
• Databricks

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