- Design enterprise-scale data platforms powering analytics and AI
- Lead automation, MLOps, and cloud data transformation initiatives
About Our Client
Our client is a technology-driven enterprise undergoing a significant data and AI transformation journey. With a strong focus on leveraging cloud platforms, advanced analytics, and machine learning, the organization is building a modern data foundation that empowers business decision-making, operational efficiency, and innovation at scale. The company offers a collaborative environment where data engineering, analytics, and AI teams work closely to deliver measurable business outcomes while embracing engineering excellence and continuous improvement.
Job Description
As a Senior Data Engineer, you will play a critical role in designing and delivering reliable, scalable, and production-grade data platforms that support business intelligence, advanced analytics, and AI initiatives.
- Design, develop, and maintain scalable data pipelines for ingestion, transformation, and delivery across multiple business domains.
- Build and automate ETL/ELT workflows using modern orchestration and cloud technologies to improve reliability and efficiency.
- Optimize enterprise data lakehouse and warehouse environments, ensuring performance, scalability, and cost effectiveness.
- Partner with Data Scientists and Analytics teams to build robust data foundations that support machine learning and AI solutions.
- Implement data quality frameworks, monitoring solutions, governance standards, and security controls across the data ecosystem.
- Enable CI/CD practices, Infrastructure-as-Code, and containerized deployment methodologies to support modern engineering standards.
- Drive continuous improvement initiatives through technology evaluation, architecture enhancements, and automation best practices.
The Successful Applicant
- Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related discipline.
- Experience in data engineering, data platform development, or large-scale data infrastructure environments.
- Strong proficiency in SQL and Python, with hands-on experience in data processing frameworks such as Spark, Hadoop, dbt, and Airflow.
- Proven expertise designing and supporting enterprise-level cloud data platforms and large-scale datasets.
- Experience with AWS data services including Redshift, Glue, S3, Athena, EMR, Lambda, and Lake Formation.
- Exposure to modern cloud analytics platforms such as Databricks and Snowflake.
- Knowledge of MLOps frameworks and tools including SageMaker, MLflow, or similar machine learning deployment platforms.
- Strong understanding of data governance, security, compliance, and data quality management practices.
- Professional certifications in cloud, data engineering, or solution architecture will be advantageous
What's on Offer
- Opportunity to shape and scale a next-generation enterprise data and AI platform.
- Exposure to cutting-edge cloud, analytics, and machine learning technologies.
- High-impact role working alongside experienced data, analytics, and engineering professionals.
- Strong emphasis on innovation, automation, and technical excellence.
- Continuous learning and professional development opportunities.
- Career progression within a growing data and digital transformation environment.
- Collaborative culture with visibility across senior business and technology stakeholders.
Contact
Quote job ref: JN-072026-7065578
