ETIC, Data Engineer, Manager

Data Engineering Manager

As a Data Engineering Manager, you will lead the design, development, and optimization of modern data platforms and pipelines on Azure and Databricks. You will oversee a team of data engineers and collaborate with cross-functional stakeholders to deliver scalable, secure, and high-performing data solutions that enable advanced analytics, AI, and business insights for enterprise clients. This role requires deep expertise in cloud data architecture, hands-on experience with Azure data services (including Microsoft Fabric), and advanced proficiency in Databricks for batch and real-time data engineering. You will also be responsible for mentoring team members, driving technical excellence, and aligning data engineering initiatives with business strategy.

Key Responsibilities

• Lead the end-to-end delivery of data engineering projects, ensuring alignment with business goals and technical standards.
• Architect and oversee the implementation of scalable data pipelines across structured, semi-structured, and unstructured data sources.
• Guide the adoption of best practices in data ingestion, transformation, and orchestration using Azure Data Factory, Synapse, and Microsoft Fabric.
• Drive performance optimization and scalability of ETL/ELT processes using Databricks (PySpark, SQL, Delta Lake).
• Establish and enforce data governance, quality, lineage, and observability frameworks.
• Collaborate with solution architects and business leaders to define modern data architectures and ensure compliance with security and privacy regulations.
• Facilitate technical workshops, stakeholder engagements, and roadmap planning sessions.
• Mentor and develop junior engineers, fostering a culture of innovation, accountability, and continuous learning.

Required Skills & Experience

• 7–10 years of experience in data engineering, with at least 3 years in a leadership or managerial role.
• Proven track record of delivering enterprise-grade data solutions in consulting or large-scale environments.
• Advanced hands-on experience with:
  • Azure Data Platform: Data Factory, Synapse Analytics, Azure Data Lake Storage, Microsoft Fabric, Event Hub/IoT Hub, Azure Functions.
  • Databricks: PySpark, Spark SQL, Delta Lake, Unity Catalog, Databricks Workflows.
• Strong proficiency in Python and SQL for large-scale data processing.
• Expertise in data modeling, medallion architecture, and lakehouse principles.
• Familiarity with CI/CD pipelines, DevOps practices, and version control systems (e.g., Git, Azure DevOps).
• Experience implementing data governance and observability tools.
• Strategic mindset with the ability to balance technical depth and business impact.

Degrees/Field of Study required: Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Transformation {+ 24 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements: Not Specified

Available for Work Visa Sponsorship? No

Government Clearance Required? No

Job Posting End Date