Senior / Lead Data Engineer (GCP Focus) at Endava

Kuala Lumpur, Kuala Lumpur, Malaysia -

Full Time

Start Date

Immediate

Expiry Date

23 Feb, 26

Salary

0.0

Posted On

25 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, GCP, AWS, Azure, Python, Apache Spark, SQL, ETL, ELT, Big Data, Data Architecture, Data Modeling, Machine Learning, Data Governance, Data Quality, Data Pipelines

Industry

IT Services and IT Consulting

Description

Company Description Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise, and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses. From prototype to real-world impact, be part of a global shift by doing work that matters. Job Description About the Role We’re looking for experienced data engineers, both senior and lead level, with strong expertise in cloud-based data solutions, ideally within Google Cloud Platform (GCP). In this role, you’ll be responsible for building, optimizing, and maintaining scalable data pipelines and architectures that support analytics, machine learning, and data-driven decision-making across the organization. While GCP experience is preferred, we also welcome candidates with AWS or Azure backgrounds who are keen to expand their hands-on experience with GCP. Fluency in Cantonese is a nice-to-have and will help in collaborating effectively with local stakeholders, but it is not a requirement. Key Responsibilities Collaborate with data analysts and data scientists to design efficient data flows, pipelines, and reporting solutions. Work closely with business stakeholders to understand data usage and identify areas for improvement. Design and implement cloud-based architecture and deployment processes on GCP (or other cloud platforms). Build and maintain data pipelines, transformations, and metadata to support business needs. Develop, test, and optimize big data solutions for scalability, performance, and reliability. Create and manage relational and dimensional data models aligned with platform capabilities. Monitor and maintain the production environment, ensuring data quality, integrity, and governance. Lead or contribute to initiatives improving data quality, governance, security, and compliance. Requirements Proven experience as a Data Engineer, ideally with GCP services (e.g., BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Storage). Experience with AWS or Azure is highly valued, especially for those eager to become more hands-on with GCP. Strong understanding of data architecture, modeling, and ETL/ELT processes. Hands-on experience with big data frameworks and modern data tools. Excellent communication and collaboration skills across technical and business teams. Familiarity with machine learning, AI, or advanced analytics is a plus. Cantonese proficiency is a nice-to-have but not mandatory. Qualifications 5+ years of experience in data engineering. Strong proficiency in Python and Apache Spark. Hands-on experience designing and implementing ETL/ELT processes and data pipelines. Solid expertise in SQL scripting and query optimization. Experience with Snowflake or other modern cloud data platforms. Background in cloud data technologies and tools, with exposure to: Data processing frameworks (Spark, Hadoop, Apache Beam, Dataproc, or similar) Data warehouses (BigQuery, Redshift, or equivalent) Real-time streaming pipelines (Kinesis, Kafka, or similar) Batch and serverless data processing Strong analytical skills with the ability to work with both structured and unstructured data. Experience in leading IT projects and managing stakeholder expectations. Additional Information Discover some of the global benefits that empower our people to become the best version of themselves: Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus; Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership; Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences; Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme; Health: Global internal wellbeing programme, access to wellbeing apps; Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations. At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.

Responsibilities

The role involves building, optimizing, and maintaining scalable data pipelines and architectures to support analytics and data-driven decision-making. Collaboration with data analysts, data scientists, and business stakeholders is essential to design efficient data flows and identify areas for improvement.