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Deputy Head, Data Engineering

Salary undisclosed

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Position Summary:

As the Deputy Head of Data Engineering, you will play a pivotal role in leading our data engineering team, driving the design, development, and maintenance of scalable data architectures. You will collaborate with cross-functional teams to ensure that data solutions align with organizational goals, enabling data-driven decision-making.

Key Responsibilities:

Team and technical leadership

  1. Draw on your past expertise to provide technical design and architecture and design the appropriate modern data stack for our level of data maturity
  2. Lead and mentor technical junior members of the team, enabling professional growth and learning

Data Infrastructure development

  1. Design and implement robust, scalable and cost-optimized data pipelines across on premise and cloud infrastructure to collect, process, and store data from various sources.
  2. Develop and maintain data pipelines and ETL processes to ensure the availability and integrity of data for analysis and modeling.
  3. Build business relevant data lake and data warehouses to support a combination of management reporting for business end-users and data science development environment for data scientist end-users.
  4. Build appropriate data governance processes and safeguards including access control and appropriate anonymization and masking.
  5. Work with cloud infrastructure team who will provision necessary data related infrastructure.

Skills & Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
  • Proven experience as a technical leader and practitioner, building and scaling data infrastructure in data engineering and/or data analytics roles and at least 10 years in the software industry.
  • Excellent problem-solving and analytical skills, with the ability to approach complex business problems in a structured and logical manner.
  • Strong familiarity and expertise with the modern data engineering (eg. SQL, Hive, Airflow, dbt, Spark), data science (e.g., pandas, numpy, scikit-learn) and data visualization technologies (Tableau, Qlik, Looker or Apache Superset).
  • Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and present technical concepts to non-technical stakeholders.
  • Proven ability to lead and mentor a team, fostering a collaborative and innovative work environment.
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