Data Engineering Manager

Responsibilities:
Focus on major areas of work, typically 20% or more of the role % of time.
Lead the successful design of complex technical problems.
Lead and contribute to the design and growth of our data products and data warehouses around content movements and metrics.
Use sophisticated analytical thought to exercise judgement and identify innovative solutions.
Partner with technical and non-technical colleagues to understand data and reporting requirements and collaborate with data product managers, data architects and others.
Data engineers to design, implement, and deliver successful data solutions.
Interviewing and hiring of new data engineers.
Determine appropriate training for data engineers and coordinate with vendors to provide it.
Serve as an advanced resource to other data engineers on the team, and mentor and coach more junior members of the team, helping to improve their skills, knowledge, and productivity.
Help create and maintain an engineering culture that embraces diversity and fosters trust and innovation in teams.
Have the ability to comprehensively document and align design with broad scope and impact.
Be a strong peer, comfortably participating in meetings at a leadership level to help drive alignment and understanding.
Requirements:
Minimum and Preferred. Inclusive of licences/certs (include functional experience as well as behavioural attributes and/or leadership capabilities).
7+ years of data engineering experience developing large data pipelines.
Strong understanding of data modelling principles, including dimensional modelling and data normalisation principles.
Good understanding of SQL Engines and Databricks.
Ability to think strategically and analyse and interpret market and consumer information.
Ability to interpret data, identify insights, and communicate actionable strategies to senior levels of the organisation.
Strong interpersonal, communication and presentation skills; experience working cross-functionally.
Proven ability to lead and drive work across cross-functional teams.
Confirmed ability to lead a team, including prioritising work and driving high-level output.
Flexible and adaptable to changing priorities and business needs.
Preferred Qualifications:
4+ years of work experience implementing and reporting on business key performance indicators in data warehousing environments.
5+ years of experience using analytic SQL, working with traditional relational databases and/or distributed systems (Snowflake or Redshift).
3+ years of experience with programming languages (e. g., Python, PySpark).
3+ years of experience with data orchestration/ETL tools (Airflow, NiFi).
Experience with Snowflake, Databricks/EMR/Spark and Airflow is a plus.

Experience
15-19 yrs