Data Engineering Manager

Key Responsibilities

IT Manager Data Engineering & Analytics

What You’ll Do

Team Leadership

• Lead, mentor, and manage a team of data engineers and analysts.
  
• Foster a culture of collaboration, accountability, and continuous learning.
  
• Conduct performance reviews, provide career guidance, and manage resource planning.
  

Data Engineering & Analytics

• Design and implement scalable, efficient data pipelines and models.
  
• Develop and enforce data quality frameworks ensuring accuracy and reliability.
  
• Maintain data lineage and robust data warehousing to support analytics and reporting.
  

Collaboration & Stakeholder Management

• Partner with stakeholders to understand business needs and translate them into technical requirements.
  
• Ensure alignment of data infrastructure with organizational goals.
  
• Build and maintain strong relationships with key stakeholders to align data strategy with business objectives.
  

Project Management

• Drive end-to-end delivery of data and analytics projects.
  
• Manage project roadmaps, prioritize tasks, allocate resources, and mitigate risks.
  

Technology & Infrastructure

• Evaluate and implement modern tools, technologies, and best practices.
  
• Oversee the design and maintenance of production data pipelines.
  
• Monitor pipeline performance, integrity, and prevent data leakage.
  
• Familiarity with tools like

  Superset

  and

  Tableau

  for building intuitive dashboards is beneficial.

Machine Learning & GenAI Integration

• Machine Learning

  : Knowledge of ML concepts and integration into pipelines to improve data quality and predictive capabilities.

• Generative AI (GenAI)

  : Exposure to GenAI tools to automate tasks, enhance workflows, and gain deeper insights from datasets.

Additional / Ad-Hoc Responsibilities

• Support special projects and cross-functional data initiatives as needed.
• 
  

What Skills Are We Looking For?

Education & Experience

• Bachelor’s/Master’s degree in Computer Science, Engineering, Data Science, or a related field.
  
• 12+ years of experience in data engineering, including at least 3 years in a leadership role.
  
• Experience in consulting or professional services environments (e.g., Accenture, Big 4) preferred.
  

Technical Skills

• Expertise in data engineering concepts: data warehousing, ETL, and pipeline design.
  
• Proficiency in

  Azure Synapse

  ,

  Data Factory

  ,

  SQL

  ,

  Python

  , and other modern tools.
• Strong experience in

  data modeling

  , architecture design, and cloud platforms (e.g.,

  Azure, Databricks).

Leadership & Communication

• Proven ability to lead engineering teams and manage cross-functional initiatives.
  
• Strong problem-solving and analytical skills.
  
• Excellent verbal and written communication to engage both technical and non-technical stakeholders.
  

Additional Competencies

• Familiarity with

  machine learning

  and

  GenAI

  integrations is a plus.
• Understanding of

  data governance

  and best practices.
• Open mindset with adaptability to emerging technologies and methodologies.