Role Overview

The purpose of this role is to design, build, and maintain scalable data pipelines and infrastructure that enable the efficient processing and analysis of large, complex data sets. This role is designed for impact, and we believe our best work happens when we connect. While we operate a flexible model, we expect you to spend time on site (at our offices or a client location) for collaboration sessions, customer meetings, and internal workshops.

Develop and maintain automated data processing pipelines using Google Cloud:
Design, build, and maintain data pipelines to support data ingestion, ETL, and storage
Build and maintain automated data pipelines to monitor data quality and troubleshoot issues
Implement and maintain databases and data storage solutions:
Stay up-to-date with emerging trends and technologies in big data and data engineering
Ensure data quality, accuracy, and completeness
Implement and enforce data governance policies and procedures to ensure data quality and accuracy:
Collaborate with data scientists and analysts to design and optimise data models for analytical and reporting purposes
Develop and maintain data models to support analytics and reporting
Monitor and maintain data infrastructure to ensure availability and performance

Requirements

What Success Looks Like

Experience in contributing to technical decision making during in-flight projects.
A track record of being involved in a wide range of projects with various tools and technologies, and solving a broad range of problems using your technical skills.
Demonstrable experience of utilising strong communication and stakeholder management skills when engaging with customers
Significant experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
Strong proficiency in SQL and experience with relational databases such as MySQL, PostgreSQL, or Oracle.
Experience with big data technologies such as Hadoop, Spark, or Hive.
Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow.
Proficiency in Python and at least one other programming language such as Java, or Scala.
Willingness to mentor more junior members of the team.
Strong analytical and problem-solving skills with the ability to work independently and in a team environment.

Tech Stack

Airflow
Amazon Redshift
Apache
AWS
Azure
BigQuery
Cloud
ETL
Google Cloud Platform
Hadoop
Java
MySQL
Oracle
Postgres
Python
Scala
Spark
SQL

Benefits

We believe in supporting our team members both professionally and personally. Here's how we invest in you:

Compensation and Financial Well-being

Competitive base salary.
Discretionary company bonus scheme.
Employee referral scheme.
Meal Vouchers.

Health and Wellness

Health Care Package.
Life and Health Insurance.

Work-Life Balance and Growth

Bookster.
28 days of annual leave.
Floating bank holidays.
An extra paid day off on your birthday.
Ten paid learning days per year.
Flexible working hours.
Sabbatical leave (after 5 years).
Work from anywhere (up to 3 weeks per year).
Industry-recognised training and certifications.
Bonusly: employee recognition and rewards platform.
Clear opportunities for career development.
Length of Service Awards.
Regular company events.

Diversity and InclusionAt Qodea, we champion diversity and inclusion. We believe that a career in IT should be open to everyone, regardless of race, ethnicity, gender, age, sexual orientation, disability, or neurotype. We value the unique talents and perspectives that each individual brings to our team, and we strive to create a fair and accessible hiring process for all.

Director, Data Engineering

Key skills

About this role