Data Engineering Manager

Data Engineering Manager

Roles & Responsibilities

• Leadership & Mentorship:

  Lead and mentor a team of data engineers, fostering a culture of innovation and continuous learning. You will guide your team in writing high-quality code and validating data ingestion, processing, and transformation techniques.

• Architecture & Pipelines:

  You will oversee the development of data extraction, validation, and transformation techniques. This includes driving the development of data tools and frameworks and overseeing the implementation of performance monitoring protocols to ensure pipeline stability and efficiency.

• Governance & Best Practices:

  Oversee

  data governance

  strategies, ensuring compliance with security policies and regulations. You will guide engineers in

  data modeling, metadata management

  , and access control. You will also stay up-to-date with emerging data technologies and industry trends.

• Agile & Strategic Collaboration:

  Drive

  Agile

  and

  Scaled Agile (SAFe)

  methodologies, handling sprint backlogs and prioritization. You will collaborate with business leaders, product owners, and cross-functional teams to align data architecture with business objectives. You will also prepare your team for key partner discussions by assessing data costs and requirements.

Qualifications

• A Master's degree with 4-6 years of experience, a Bachelor's degree with 6-8 years of experience, or a Diploma with 10-12 years of experience in Computer Science, IT, or a related field. A Doctorate degree is also accepted.
• Experience leading a team of data engineers in the

  R&D

  domain of biotech/pharma companies.
• Demonstrated hands-on experience with cloud platforms (

  AWS, GCP, or Azure

  ) and the ability to architect cost-effective and scalable data solutions.
• Proficiency in

  Python, PySpark

  , and

  SQL

  .
• Experience with dimensional data modeling and working with tools like

  Apache Spark

  and

  Apache Airflow

  .
• Experience with software engineering best practices, including version control (

  Git

  ),

  CI/CD

  , and

  DevOps

  .
• Certifications such as

  AWS Certified Data Engineer, Databricks Certificate

  , or

  Scaled Agile SAFe

  are a plus.

Soft Skills

• Leadership:

  Strong leadership, presentation, and public speaking skills, with the ability to handle multiple priorities successfully.

• Problem-Solving:

  Strong analytical and problem-solving skills to address complex data challenges.

• Communication:

  Excellent verbal and written communication skills to collaborate effectively with cross-functional and global teams.

• Initiative:

  A high degree of initiative and self-motivation, with a focus on achieving team goals.