Senior Data Engineer

Join a forward-thinking organization that is investing heavily in modern data platforms, advanced analytics, and artificial intelligence capabilities. This role offers the opportunity to architect scalable data ecosystems, enable AI innovation, and drive enterprise-wide data excellence through automation and cloud technologies.

Client Details

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.

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.

Profile

• 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

Job 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.