Job Title: Senior Data Engineer – Cloud (GCP)

Location: [Location]
Job Type: [Contract]
Experience Required: 7+ years

Job Description:
We are seeking an experienced Senior Data Engineer with expertise in cloud architecture and data engineering, specifically within the Google Cloud Platform (GCP) ecosystem. The ideal candidate will have extensive experience in developing scalable and reliable data solutions, working with various data engineering tools, and delivering complex data transformations. This position requires a strong background in cloud-native technologies, data pipelines, and machine learning operations (MLOps).

As part of the team, you will work closely with cross-functional teams to design and implement scalable data architectures that meet business needs and improve data management across the organization.

Key Responsibilities:

• Design, build, and maintain scalable and reliable cloud-based data systems on GCP.
• Develop, test, and deploy ETL pipelines using tools like Apache Airflow, Cloud Composer, and DataFlow.
• Implement and manage large-scale data transformations using GCP BigQuery, Hadoop, Hive, Spark, and other cloud-native services.
• Develop and maintain Python scripts for data processing and automation.
• Create and optimize data architecture and infrastructure, ensuring high availability, scalability, and performance.
• Lead the design and implementation of data quality controls and user-friendly interfaces to manage data workflows.
• Collaborate with business and technical teams to understand requirements and deliver tailored data solutions.
• Design and implement dashboards and reporting solutions using Looker and LookML.
• Work in an Agile environment, iterating quickly and delivering value while ensuring quality.
• Stay up-to-date with emerging trends and technologies in cloud data engineering and MLOps.
• Mentor and support junior engineers, fostering a collaborative and innovative team culture.

Key Skills and Requirements:

• 8+ years of experience in cloud application architecture and data engineering.
• Strong experience (5+ years) working with Google Cloud Platform (GCP), specifically GCP BigQuery, Data Flow, Cloud Composer, and other cloud-native services.
• Expertise in building and managing ETL pipelines, using tools such as Apache Airflow and Cloud Composer.
• Solid programming skills in Python, with a focus on automation, data manipulation, and optimization.
• Experience with Hadoop, Hive, HDFS, Spark, YARN, and Scala for data processing and transformation.
• Proven experience (5+ years) designing and implementing data architectures, including Data Mesh and Cloud Data Architecture.
• Knowledge of Linux/Unix systems and scripting (PL/SQL, Bash, etc.).
• Expertise in using MLOps frameworks to operationalize machine learning models and data pipelines.
• Experience with data visualization and reporting tools, particularly Looker and LookML.
• Strong knowledge of operating systems like Windows and Linux.
• Deep understanding of data governance, compliance, and reporting standards.
• Familiarity with data modeling, Alteryx pipelines, and Qlik management is a plus.
• Bachelor’s degree in Computer Science or a related field.
• Strong problem-solving and analytical skills with a keen attention to detail.
• Ability to collaborate effectively in a team-oriented, Agile environment.

Preferred Skills:

• Expertise in managing AWS services such as EC2, Lambda, and relational databases.
• Experience with building and optimizing dashboards for data-driven decision-making.
• Knowledge of operating systems like Windows and Linux.
  
  Additional Information:

This role is part of a world-leading bank's program to enhance data management practices, with a focus on improving operational efficiency and driving data-driven decision-making. Join a dynamic, multi-skilled team working on a high-impact project that will shape the future of data at an enterprise scale.