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.

Skills

Airflow, Databricks, ETL, NiFi, PySpark, Python, Redshift, SQL, Snowflake, Spark, data engineering, pipelines