Lead Data Engineer

🕒 June 5

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Brillio

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🤖 Artificial Intelligence

🔒 Cybersecurity

💰 Private Equity Round on 2019-01

Artificial Intelligence • Consulting • Cybersecurity

Brillio is a technology consulting company that specializes in driving digital transformation for businesses across various industries such as banking, financial services, insurance, life sciences, telecom and media, healthcare, and retail. They focus on customer experience transformation, data and AI, product and platform engineering, and provide infrastructure, cloud, and security solutions. With an emphasis on engineering digital products and leveraging generative AI, Brillio aims to provide bespoke solutions that help businesses thrive in the age of AI and technological disruption. They also offer services to help businesses adapt to new technological challenges and turn disruptions into competitive advantages.

📋 Description

• Design, develop, and maintain scalable and reliable data pipelines, ETL/ELT frameworks, and data integration solutions. • Build cloud-native data solutions using AWS services including Glue, Lambda, Redshift, Aurora, OpenSearch, Step Functions, SNS, and S3. • Develop and optimize data processing workflows using Python, PySpark, SQL, and PL/SQL. • Design and implement data warehouse solutions, data marts, and data models to support enterprise reporting and analytics. • Work closely with business stakeholders, product teams, data scientists, and analysts to understand requirements and deliver high-quality data solutions. • Ensure data quality, integrity, governance, security, and compliance across the data ecosystem. • Optimize database performance, query execution, and large-scale data processing workloads. • Implement monitoring, alerting, and troubleshooting mechanisms to ensure platform reliability and operational excellence. • Participate in solution design discussions, architecture reviews, and cloud modernization initiatives. • Mentor junior team members and promote engineering best practices, code quality standards, and knowledge sharing. • Support production deployments, issue resolution, and continuous improvement activities.

🎯 Requirements

• 8–10 years of experience in Data Engineering, Data Warehousing, and Cloud Data Platform development. • Proven experience delivering enterprise-scale data engineering solutions in cloud environments. • Strong hands-on experience with: AWS Glue, Lambda, Redshift, Aurora, OpenSearch, Step Functions, SNS, S3 • Advanced proficiency in Python and PySpark for large-scale data processing. • Strong expertise in SQL and PL/SQL development. • Experience building and optimizing ETL/ELT pipelines and data ingestion frameworks. • Solid understanding of data warehousing concepts, dimensional modeling, and database design. • Experience working with structured, semi-structured, and unstructured data. • Strong understanding of modern data architectures, including Data Lakes and Data Warehouses. • Experience designing scalable, secure, and high-performance data solutions. • Knowledge of data quality frameworks, governance practices, and data lifecycle management. • Experience with workflow orchestration, event-driven architectures, and distributed data processing. • Strong analytical and problem-solving capabilities. • Excellent communication and stakeholder management skills. • Ability to work independently and collaboratively in a fast-paced environment. • Strong ownership mindset with a focus on quality, reliability, and continuous improvement. • Experience supporting Data Science, Machine Learning, AI, or Advanced Analytics initiatives. • Exposure to modern Data Lakehouse architectures. • Experience with CI/CD pipelines, DevOps practices, and Infrastructure as Code (IaC). • Experience working in Agile/Scrum delivery environments. • AWS Certifications such as AWS Certified Data Engineer, Solutions Architect, or equivalent cloud certifications.